דרושים Team Lead Master Data Management ב-Intercontinental Exchange - Ice ב-India, Hyderabad

Job Purpose

The Property Data Engineer is responsible for developing and maintaining data conversion programs that transform raw property assessment data into standardized formats based on specifications by Property Data Analyst and Senior Analysts. This role requires not only advanced programming and ETL skills but also a deep understanding of the structure, nuances, and business context of assessment data. Even with clear and well-documented conversion instructions, engineers without prior exposure to this domain often face significant challenges in interpreting and transforming the data accurately. Data Engineer plays a critical role in ensuring the accuracy, efficiency and scalability of data processing pipelines that support the Assessor Operations.

Responsibilities

Depending on the specific team and role, the Property Data Engineer may be responsible for some or all the following tasks:

• Develop and maintain data conversion programs using C#, Python, JavaScript, and SQL.
• Implement ETL workflows using tools such as Pentaho Kettle, SSIS, and internal applications.
• Collaborate with Analysts and Senior Analysts to interpret conversion instructions and translate them into executable code.
• Troubleshoot and resolve issues identified during quality control reviews.
• Recommend and implement automation strategies to improve data processing efficiency.
• Perform quality checks on converted data and ensure alignment with business rules and standards.
• Contribute to the development of internal tools and utilities to support data transformation tasks.
• Maintain documentation for code, workflows, and processes to support team knowledge sharing.

Programming (Skill Level: Advanced to Expert)

• Create and maintain conversion programs in SQL, Visual Studio using C#, Python or JavaScript.
• Use JavaScript within Pentaho Kettle workflows and SSIS for data transformation.
• Build and enhance in-house tools to support custom data processing needs.
• Ensure code is modular, maintainable, and aligned with internal development standards.
• Ensure code quality through peer reviews, testing and adherence to development standards.

ETL Execution (Skill Level: Advanced to Expert
)

• Execute and troubleshoot ETL processes using tools like Kettle, SSIS, and proprietary tools.
• Input parameters, execute jobs, and perform quality checks on output files.
• Troubleshoot ETL failures and optimize performance.
• Recommend and implement automation strategies to improve data processing efficiency and accuracy.

Data File Manipulation (Skill Level: Advanced to Expert)

• Work with a wide variety of file formats (CSV, Excel, TXT, XML, etc.) to prepare data for conversion.
• Apply advanced techniques to clean, merge, and structure data.
• Develop scripts and tools to automate repetitive data preparation tasks.
• Ensure data is optimized for downstream ETL and analytical workflows.

Data Analysis (Skill Level: Supportive – Applied)

• Leverage prior experience in data analysis to independently review and interpret source data when developing or refining conversion programs.
• Analyze data structures, field patterns, and anomalies to improve the accuracy and efficiency of conversion logic.
• Use SQL queries, Excel tools, and internal utilities to validate assumptions and enhance the clarity of analyst-provided instructions.
• Collaborate with Analysts and Senior Analysts to clarify ambiguous requirements and suggest improvements based on technical feasibility and data behavior.
• Conduct targeted research using public data sources (e.g., assessor websites) to resolve data inconsistencies or fill in missing context during development.

Quality Control (Skill Level: Engineer-Level)

• Perform initial quality control on converted data outputs before formal review by Associates, Analysts, or Senior Analysts for formal review.
• Validate that the program output aligns with conversion instructions and meets formatting and structural expectations.
• Use standard scripts, ad-hoc SQL queries, and internal tools to identify and correct discrepancies in the data.
• Address issues identified during downstream QC reviews by updating conversion logic or collaborating with analysts to refine requirements.
• Ensure that all deliverables meet internal quality standards prior to release or further review.

Knowledge and Experience

• Minimum Education: Bachelor’s degree in Computer Science, Information Systems, Software Engineering, Data Engineering, or a related technical field; or equivalent practical experience in software development or data engineering.
• Preferred Education: Bachelor’s degree (as above) plus additional coursework or certifications in:
  • Data Engineering
  • ETL Development
  • Cloud Data Platforms (e.g., AWS, Azure, GCP)
  • SQL and Database Management
  • Programming (C#, Python, JavaScript)
• 4+ years of experience in software development, data engineering, or ETL pipeline development.
• Expert-level proficiency in programming languages such as SQL, Visual Studio using C#, Python, and JavaScript.
• Experience with ETL tools such as Pentaho Kettle, SSIS, or similar platforms.
• Strong understanding of data structures, file formats (CSV, Excel, TXT, XML), and data transformation techniques.
• Familiarity with relational databases and SQL for data querying and validation.
• Ability to read and interpret technical documentation and conversion instructions.
• Strong problem-solving skills and attention to detail.
• Ability to work independently and collaboratively in a fast-paced environment.
• Familiarity with property assessment, GIS, tax or public property records data.

Preferred Skills

• Experience developing and maintaining data conversion programs in Visual Studio.
• Experience with property assessment, GIS, tax or public records data.
• Experience building internal tools or utilities to support data transformation workflows.
• Knowledge of version control systems (e.g., Git, Jira) and agile development practices.
• Exposure to cloud-based data platforms or services (e.g., Azure Data Factory, AWS Glue).
• Ability to troubleshoot and optimize ETL performance and data quality.
• Strong written and verbal communication skills for cross-functional collaboration.

Responsibilities

• Lead Business Analysis Initiatives: Direct and prioritize the activities of the business analysis team to ensure alignment with organizational objectives and project timelines.
• Stakeholder Engagement: Act as the primary liaison between business units, technology teams, data operations and product teams, facilitating clear communication and efficient resolution of business needs.
• Requirements Gathering & Documentation: Oversee the comprehensive collection, validation, and documentation of business and functional requirements for reference data projects.
• Data Governance & Quality: Advocate and implement reference data governance frameworks to guarantee data integrity, compliance, and consistency across platforms.
• Process Improvement: Identify inefficiencies in current data operations processes and lead cross-functional initiatives to optimize workflows and increase automation where possible.
• Project Management: Manage multiple complex projects simultaneously, ensuring timely and budget-conscious delivery of milestones and deliverables.
• Team Leadership & Development: Mentor, coach, and develop business analysts and data specialists, fostering a culture of continuous learning and high performance.
• Change Management: Lead organizational change initiatives related to data Integration, ensuring successful adoption of new processes, tools, and technologies.
• Risk Management: Proactively identify and mitigate risks related to data accuracy, accessibility, and regulatory compliance.
• Reporting & Analytics: Deliver actionable insights through the design and interpretation of management reports, dashboards, and key performance indicators (KPIs).
• Vendor & Third-Party Management: work closely with vendors and third parties on board and integrate their data on a timely and efficient basis.

Knowledge and Experience

• Education: Bachelor’s degree in business administration, Finance, Economics, Information Systems, Computer Science, or a related field. An advanced degree (MBA, MS, or equivalent) is highly desirable.
• Experience: Minimum of 8-10 years of progressive experience in business analysis, reference data management, or data operations in financial services, asset management, or a similar sector.
• Technical Expertise: Demonstrated proficiency in data management tools, SQL and data modeling. Proven experience with python on the daily work cycle to improve and automate data integration projects.
• Project Management: Proven track record managing large-scale, cross-functional data projects with multiple stakeholders and competing priorities.
• Analytical Skills: Advanced analytical and quantitative skills, with the ability to interpret complex data sets and present findings to business leaders.
• Communication: Exceptional written and verbal communication skills, with the ability to translate technical concepts for non-technical audiences.
• Leadership: Proven ability to inspire, develop, and lead high-performing teams in a fast-paced, dynamic environment.
• Change Management: Experience implementing change and driving user adoption of new systems or processes.
• Vendor Management: Experience managing relationships with data vendors or third-party service providers.
• Tools & Platforms: Experience with data visualization tools (such as Tableau or Power BI), workflow management solutions, and enterprise data management platforms.

Preferred Knowledge and Experience

• Certifications: Professional certification in Business Analysis, Data Management, or Project Management.
• Industry Experience: Direct experience in investment banking, asset management, or securities operations.
• Technology Acumen: Experience with cloud data platforms (AWS, Azure), data lakes, and advanced analytics solutions.

Key Competencies and Attributes

• Strategic Thinking: Sees the "big picture" and translates vision into actionable business and data strategies.
• Problem Solving: Tackles complex challenges with methodical, data-driven approaches and innovative thinking.
• Attention to Detail: Ensures accuracy and thoroughness in data analysis, documentation, and process design.
• Resilience: Remains effective under pressure and adapts quickly to evolving priorities and constraints.
• Collaboration: Builds strong relationships across business and technology teams, promoting a culture of partnership and shared success.
• Ethics and Integrity: Adheres to the highest standards of professional conduct, confidentiality, and regulatory compliance.
• Customer Focus: Anticipates internal and external client needs and delivers solutions that drive business value.

Job Purpose

AIP Suites (Data Modernization to Snowflake) builds an analytics-ready data architecture where data from source systems such as PDM (Product Data Management) and RDO is ingested into Snowflake for centralized storage and modeling. These models support ICE BI, which consumes Snowflake data for analytics and dashboarding. This design ensures clean separation between raw ingestion, transformation, analytics, and service-based consumption, supporting scalable and future-proof data-driven operations.

Responsibilities

• Provides Snowflake-based data warehouse design and development for projects involving new data integration, migration, and enhancement of existing pipelines.
• Designs and develops data transformation logic using SQL, Snowflake stored procedures, and Python-based scripts for ETL/ELT workloads.
• Builds and maintains robust data pipelines to support reporting, analytics, and application data needs.
• Creates and maintains Snowflake objects like tables, views, streams, tasks, file formats, and external stages.
• Participates in project meetings with data engineers, analysts, business users, and product owners to understand and implement technical requirements.
• Writes technical design documentation based on business requirements and data architecture principles.
• Develops and/or reviews unit testing protocols for SQL scripts, procedures, and data pipelines using automation frameworks.
• Completes documentation and procedures for pipeline deployment, operational handover, and monitoring.
• May mentor or guide junior developers and data engineers.
• Stays current with Snowflake features, best practices, and industry trends in cloud data platforms.
• Performs additional related duties as assigned.

Knowledge and Experience

• Bachelor’s Degree or the equivalent combination of education, training, or work experience.
• 5+ years of professional experience in data engineering or database development.
• Strong Hands-on experience:
• Writing complex SQL queries and stored procedures
• Database stored procedures, functions, views, and schema design
• Using Streams, Tasks, Time Travel, and Cloning
• Proficiency in database performance tuning and performance optimization — clustering, warehouse sizing, caching, etc.
• Experience configuring external stages to integrate with cloud storage (AWS S3, Azure Blob, etc.).
• Experience writing Python/Shell scripts for data processing (where needed).
• Knowledge on Snowflake and Tidal is an added advantage
• Proficiency in using Git and working within Agile/Scrum SDLC environments.
• Familiarity working in a Software Development Life Cycle (SDLC) leveraging Agile principles.
• Excellent analytical, decision-making, and problem-solving skills.
• Ability to multitask in a fast-paced environment with a focus on timeliness, documentation, and communication with peers and business users.
• Strong verbal and written communication skills to engage both technical and non-technical audiences at various organizational levels.

Responsibilities

• Work with the MRM group to validate and support models, methodologies, and reporting of risks throughout the organization
• Produce and analyze validation reports by extracting meaningful insights from data and synthesize them into a compelling validation narrative
• Provide detailed analysis and documentation of methods, techniques, and findings
• Ensure the clarity, consistency, and accuracy of model validation reports by applying strong technical writing skills to articulate key takeaways
• Develop and deliver engaging presentations of analytical findings to stakeholders
• Identify opportunities for improvement and automation in reports and implement enhancements as needed
• Engage with domain experts to develop and refine risk best practices, policies, and procedures

Knowledge and Experience

• Master’s degree or higher in Economics, Finance, Statistics, Mathematics or related field
• Strong analytical and problem-solving skills with a solid understanding of statistical concepts - descriptive statistics, data visualization, probability, distributions, linear models, time series, etc.
• Competent in programming with either Python or R, as well as SQL
• Excellent presentation, verbal communication, and business writing skills
• Demonstrated ability in data exploration and critical thinking, with a keen eye for detail

Preferred

• At least 2 years of experience with financial/economic data analysis
• Demonstrated progress towards industry certifications, such as FRM and CFA
• Working knowledge of Tableau for visual analytics

Job Purpose

ICE Clear Europe’s Clearing Risk Department (“CRD”) is looking for a front office risk analyst. The successful candidate will assist the senior risk managers in overseeing and shaping the risk management practice at one of the largest futures and options clearing houses in the world. You will be joining a very dynamic team, be exposed to a wide range of asset classes and be challenged with complex risk problems. You will be responsible for carrying out all aspects of the day-to-day risk management duties and assist in developing and implementing enhancements to the risk management tools, and processes. You will also participate in the design and implementation of new risk initiatives and products that benefit the business.

Responsibilities

• Analyze and monitor market and collateral risks on real-time basis and appropriately escalate any risk concerns
• Build and maintain risk management reports to support day to day risk management, and management reporting for various ICE Clear Europe Boards and Committees.
• Ensure the risk management framework and risk policies are being adhered to and are consistent with regulatory and industry standards
• Assist with identifying areas where the risk management processes, or infrastructure can be improved
• Enhance documentation of risk processes and procedures
• Assist with internal and external communication including, inter alia, representatives from clearing members, ICE management and regulators
• Collaborate with a group of colleagues on various strategic projects
• Conduct project work and run thematic or ad-hoc market research on relevant risk topics

Knowledge and Experience

• Degree in Business, Science, Economics, Engineering, or a related numerical discipline
• Attention to detail and strong problem-solving skills with the ability to balance trade-offs
• Prior experience in risk management as a risk analyst or relevant professional experience (at an investment bank, hedge fund or clearing house) will be an advantage.
• Strong knowledge in financial derivatives products in multiple asset classes preferred
• Prior experience in applying risk management models and techniques such as Value at Risk models, Liquidity Risk models, backtesting and stress testing models will be an advantage.
• Ability to be a team player and to collaborate with other teams
• Ability to conduct research, analyze problems, formulate and implement solutions in an efficient, effective, and independent manner
• Excellent written and verbal communication skills
• Experience with SQL and Python preferred
• Experience with BI tools such as Tableau is desirable
• Any progress towards CFA or FRM would be advantageous

Job Purpose

ICE Mortgage Technology is the leading cloud-based platform provider for the mortgage finance industry. ICE Mortgage Technology solutions enable lenders to originate more loans, reduce origination costs, and reduce the time to close, all while ensuring the highest levels of compliance, quality, and efficiency.

A background in financial services (specifically mortgages and lending) is required along with operational experience.

Responsibilities

• Manage a team of Team Leader’s providing Data and Document Services to US based mortgage companies.
• Ability to train and mentor Data and Document Lead / associate.
• Collaborate with cross functional teams.
• Oversee the activities of the team and optimize their performance daily.
• Act as escalation point for the Team Leader to overcome any obstacles to service delivery.
• Ensure that Data Security is maintained.
• Demonstrate strong follow-through and consistently keep commitments to customers and Employees.
• To manage Jira and Salesforce Tickets.
• Assist reporting Manager in day-to-day activities i.e., SLA Management, Staffing Management, Administrative responsibilities, Recruitment, Retention, Review, Performance Management, Removal etc.
• To carry out above function for the team during day shift and/or night shift as circumstances may warrant.
• SOW / Contract Delivery
• Product feedback & Client Feedback Management
• New Product adoption and roll out
• Connection with PSO team / Product team / cross functional teams ; including decision making
• Client engagement and on-boarding.
• Responsible to Drive / Monitor training.
• Client level monitoring and reporting of Quality of delivery

Knowledge and Experience

• Bachelor’s degree ( Non-Technical, should not be BCA, BBA or BTech) or academic equivalent
• 7 or more years of experience in the mortgage lending or financial services market
• 3 or more years of experience managing a small- or mid-sized BPO/kpo team.
• Broad understanding of cloud technologies
• Proficiency with Microsoft Office (Excel and Word) and Microsoft Windows
• Ability to document standard procedures, and effectively train and motivate employees.
• Strong written and verbal communication skills
• Strong problem solving and decision-making skills.
• Excellent time management and organizational skills
• Ability to work efficiently and independently.
• Ability to work under pressure and time constraints, handling multiple tasks simultaneously.
• Initiative and strong sense of ownership.
• People management.
• Leadership skills.
• Proven ability to create and maintain strong customer relationships.
• Must be comfortable communicating with both technical and non-technical audiences.

Job Purpose

AIP Suites (Data Modernization to Snowflake) builds an analytics-ready data architecture where data from source systems such as PDM (Product Data Management) and RDO is ingested into Snowflake for centralized storage and modeling. These models support ICE BI, which consumes Snowflake data for analytics and dashboarding. This design ensures clean separation between raw ingestion, transformation, analytics, and service-based consumption, supporting scalable and future-proof data-driven operations.

Responsibilities

• Provides Snowflake-based data warehouse design and development for projects involving new data integration, migration, and enhancement of existing pipelines.
• Designs and develops data transformation logic using SQL, Snowflake stored procedures, and Python-based scripts for ETL/ELT workloads.
• Builds and maintains robust data pipelines to support reporting, analytics, and application data needs.
• Creates and maintains Snowflake objects like tables, views, streams, tasks, file formats, and external stages.
• Participates in project meetings with data engineers, analysts, business users, and product owners to understand and implement technical requirements.
• Writes technical design documentation based on business requirements and data architecture principles.
• Develops and/or reviews unit testing protocols for SQL scripts, procedures, and data pipelines using automation frameworks.
• Completes documentation and procedures for pipeline deployment, operational handover, and monitoring.
• May mentor or guide junior developers and data engineers.
• Stays current with Snowflake features, best practices, and industry trends in cloud data platforms.
• Performs additional related duties as assigned.

Knowledge and Experience

• Bachelor’s Degree or the equivalent combination of education, training, or work experience.
• 5+ years of professional experience in data engineering or database development.
• Strong Hands-on experience:
• Writing complex SQL queries and stored procedures
• Database stored procedures, functions, views, and schema design
• Using Streams, Tasks, Time Travel, and Cloning
• Proficiency in database performance tuning and performance optimization — clustering, warehouse sizing, caching, etc.
• Experience configuring external stages to integrate with cloud storage (AWS S3, Azure Blob, etc.).
• Experience writing Python/Shell scripts for data processing (where needed).
• Knowledge on Snowflake and Tidal is an added advantage
• Proficiency in using Git and working within Agile/Scrum SDLC environments.
• Familiarity working in a Software Development Life Cycle (SDLC) leveraging Agile principles.
• Excellent analytical, decision-making, and problem-solving skills.
• Ability to multitask in a fast-paced environment with a focus on timeliness, documentation, and communication with peers and business users.
• Strong verbal and written communication skills to engage both technical and non-technical audiences at various organizational levels.