Data Researcher jobs at Intercontinental Exchange - Ice in 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.

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.

Job Purpose

The Senior Data Quality Analyst will be responsible for developing, maintaining, and automating tests to ensure all data feeds and compliance reports and system is accurate and complete. This role requires frequent interaction with software developers, testers, product managers, compliance and market supervision professionals to ensure delivery of data quality and reports to internal and external users for business decision-making and government compliance needs. Additionally, the role will involve data analysis and automation using Python coding to enhance the efficiency and accuracy of compliance reporting.

Responsibilities

• Gather information from disparate systems to aid problem resolution
• Work with Business Analysts, Java and SQL Development engineers to review technical requirements and produce test strategies, test scenarios, and test cases to validate the correctness of data in applications and reports
• Validate transformation logic; diagnostic and debugging skills. Perform various data reconciliations
• Write, execute, and debug SQL queries to perform data completeness, correctness, data transformation, and data quality testing
• Test Java based applications
• Ensure content and structure of all testing documents/artifacts are documented and maintained
• Perform all aspects of verification, including functional, structural, regression, and system testing.
• Work in an agile environment with an iterative approach to development.

Knowledge and Experience

• Bachelor’s Degree or equivalent
• 5+ years of experience in software testing, with 3 years of experience in backend data validation which involves complex SQL
• Exposure to executing automation test scripts on Java/Selenium
• Strong background in functional testing with the ability to design and develop test strategy and test cases
• Proficiency in SQL and database systems
• Excellent attention to detail
• Proficiency in either Python coding or automation of front-end applications using Java/Selenium
• Experience with Shell Scripting and Unix
• Track record of completing assignments on time with a high degree of quality
• Excellent analytical, problem-solving, communication, and interpersonal skills
• Ability to set priorities and multi-task in a fast-paced environment
• Extensive knowledge of testing process, testing methodology analysis, and defect reporting tools
• Ability to work independently and productively under pressure
• Strong organizational skills and decision-making ability

Responsibilities

• Identify, research, and analyze data so that it can be accurately processed.
• Perform analysis and document/revise conversion requirements to translate data sets into standardized formats.
• Perform detailed data verification and analysis on issues that need to be fixed. Responsible for the escalation and resolution of data issues.
• Make process and/or system improvement recommendations to assist the business unit in achieving its goals and objectives.
• Gather reporting requirements for change requests and ad-hoc reports as requested.
• May assist with extraction, transforming, and standing up of various data sets.
• Performs other related duties as assigned.

Knowledge and Experience

• Proficient written and oral communication skills in dealing with employees or external customers/clients
• Proficiency in standard office software, such as MS Office, MS Access, MS Word, MS Excel, etc.
• Demonstrated experience with data and analysis
• Working knowledge of relational databases, a plus
• Ad-hoc SQL query development a plus
• Preferred Experience working with data analytics-driven solutions with sensitive data sources
• High degree of creative, analytical, and problem-solving skills
• Ability to gather and interpret information and to develop, recommend and implement