Data Center Technician jobs in United States, New York, New York

Your key responsibilities

You will be part of diverse teams of professionals across different geographies to deliver a wide range of data and analytics services. You will be solving complex issues and driving growth across financial services.

Skills and attributes for success

• Fostering an innovative and inclusive team-oriented work environment
• Leading and coaching diverse teams of professionals with different backgrounds
• Providing subject matter expertise in defining technical and business approaches
• Working across and influencing different stakeholders within the client organization, cultivating, and executing on business opportunities
• Building strong relationships with the clients including engaging with C-level executives and technical clients
• Initiating and building thought leadership through white papers, point of views, and proof of concepts
• Working in an entrepreneurial environment to pave your own career path
• Propose and drive new technologies to enhance or replace existing business processes

To qualify for the role, you must have

• Undergraduate or master’s degree in a quantitative field (e.g., engineering, computer science, business, economics, finance, statistics, and/or analytics)
• Minimum of 9 years’ experience in banking, capital markets, insurance, or asset management domain with at least 3 years of experience managing a team
• Superior communication (verbal and written) with the ability to effectively advocate technical solutions and results to technology and business audiences at all levels and disciplines within EY and client organizations
• Experience working independently, efficiently, and effectively under extreme time constraints and delivering results by critical deadlines
• Demonstrate exploration of new techniques outside of day-to-day job duties
• Experience presenting technical conclusions to senior officials in a company and other stakeholders
• Strong analytical and problem-solving skills
• Experience with client-facing activities such as requirements gathering, facilitating meetings, presentation creation, and ability to prepare client ready deliverables
• Project management and process development expertise in client serving roles
• Excellent leadership and teaming skills
• Strong organizational and time-management skills
• Ability to integrate new knowledge and adapt to change with a natural curiosity and desire to learn
• A willingness and ability to travel to meet client needs; travel is estimated at 60%
• Valid passport

DAE Specific

• Ability to understand business challenges and address remediations through data architecture and engineering solutions.
• Must have practical experience assisting clients with one or more of strategic Data Architecture and Engineering, Cloud Data Modernization, Data migration and Event-driven architecture, preferably focused on financial services.
• Experience architecting and designing large data platforms, data warehouses and data lakes, streaming applications, data ingestion, integration, and distribution pipelines.
• Practical experience using latest technologies for data ingestion, integration, transformation, storage, mining/warehousing, big data analytics, and visualization.
• Deep understanding of traditional data architecture practices (data warehousing, datahub, MDM, ODS etc.) as well transition to Next-Gen platform architectures such as distributed data lake and Data mesh on cloud, etc.
• Practitioner experience in multiple data technologies such as:
• Cloud Data Platforms (AWS, Azure, Google Platform, Databricks, Snowflake)
• Big Data applications and Distributed Processing (Hadoop and Spark ecosystem components)
• Data integration Tools (Informatica, Talend, etc.)
• Experience with scripting languages: Python, Java, C++, Scala, etc.
• Traditional RDBMS (Teradata, Netezza, MS SQL Server, Oracle, MySQL, PostgreSQL)
• MPP (Snowflake, BigQuery, AWS Redshift etc.)
• NoSQL (MongoDB, DynamoDB, Cassandra, Neo4J, Titan, Elasticsearch)
• Streaming Platform and Applications (Spark streaming, Kafka, Storm, etc.)
• Experience with data pipeline and workflow management tools (Airflow, etc.)
• Dev Ops (GitHub, Kubernetes Jenkins, Terraform)
• Data Modeling (Data vault, Star, Snowflake)

Ideally, you’ll also have

• Master’s degree in business administration (MBA) or Science (MS) preferred
• Prior consulting experience
• Experience monitoring performance, reporting, and economics of ongoing progress for the major initiatives of the business unit you support.
• Oral presentation skills, with the ability to lead meetings & hold workshops with executives
• Experience quantifying results to the business, from the front line to senior executives

What we offer you

: Associate-National-SaT-SaT - TCF - Capital and Debt Advisory - Mumbai

SaT - TCF - Capital and Debt Advisory :

Whether clients are preserving, optimizing, raising or investing, our Connected Capital Solutions (CCS) are our five go-to-market offerings that help drive competitive advantage and increased returns through improved decision-making. The CCS include Strategy, Corporate Finance, Buy and Integrate, Sell and Separate and Reshaping Results, and are underpinned by our Connected Capital Technologies.

Technical Excellence

• Conducting in-depth financial analysis and identifying key areas of concern
• Developing tailored strategies to address financial and operational challenges
• Collaborating with stakeholders, including lenders, investors, and management, to facilitate negotiations
• Monitoring key performance indicators and reporting progress to clients and senior management
• Assisting in the preparation of improvement plans and business recovery models
• Drive PMO for fast-track strategy implementation

Qualification

• Educational qualifications: Chartered Accountant (CA) or Master of Business Administration (MBA) from a reputed institution
• Strong technical skills – Corporate Finance
• Strong analytical and problem-solving skills
• Proficient in excel business modelling, BI tools
• Excellent communication and stakeholder management abilities
• Ability to think and drive next steps
• Willingness to travel

Experience

• Experience: 3-6 years of relevant experience in corporate

People with the ability to work in a collaborative manner to provide services across multiple client departments while following the commercial and legal requirements. You will need a practical approach to solving issues and complex problems with the ability to deliver insightful and practical solutions. We look for people who are agile, curious, mindful, and able to sustain positive energy, while being adaptable and creative in their approach.If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible.

Your key responsibilities

You will be part of diverse teams of professionals across different geographies to deliver a wide range of data and analytics services. You will be solving complex issues and driving growth across financial services.

Skills and attributes for success

• Fostering an innovative and inclusive team-oriented work environment
• Leading and coaching diverse teams of professionals with different backgrounds
• Providing subject matter expertise in defining technical and business approaches
• Building strong relationships with the clients and cultivating business opportunities
• Initiating and building thought leadership through white papers, point of views, and proof of concepts
• Working in an entrepreneurial environment to pave your own career path

To qualify for the role, you must have

• Undergraduate or master's degree in a quantitative field (e.g. engineering, computer science, business, economics, finance, statistics, and/or analytics)
• Around 6 or more years of related work experience in banking, capital markets, insurance, or asset management space
• Good communication (verbal and written) with the ability to effectively advocate technical solutions and results to technology and business audiences at all levels and disciplines within EY and client organizations
• Experience working independently, efficiently, and effectively under extreme time constraints and delivering results by critical deadlines
• Strong analytical and problem-solving skills
• Experience with client-facing activities such as requirements gathering, facilitating meetings, presentation creation, and ability to prepare client ready deliverables
• Prior experience in project management and client serving roles
• Excellent leadership and teaming skills
• Strong organizational and time-management skills
• Ability to integrate new knowledge and adapt to change with a natural curiosity and desire to learn
• A willingness and ability to travel to meet client needs; travel is estimated at 60%
• Valid passport

DAE Specific

• Ability to understand business challenges and address remediations through data architecture and engineering solutions
• Must have practical experience assisting clients with one or more of strategic Data Architecture and Engineering, Cloud Data Modernization, Big Data initiatives and Event-driven architecture, preferably focused in financial services
• Experience architecting and designing large data platforms, data warehouses, streaming applications, data ingestion, integration, and distribution pipelines
• Practical experience using latest technologies for data ingestion, integration, transformation, storage, mining/warehousing, big data analytics, and manipulation
• Deep understanding of traditional data architecture practices (MDM, ODS, data warehousing, etc.) as well transition to Next-Gen platforms such as Hadoop, Cloud, distributed ledgers, etc.
• Practitioner experience in multiple data technologies such as:

• Cloud Data Platforms (AWS, Azure, Google Platform, Databricks, Snowflake)
• Big Data applications and Distributed Processing (Hadoop ecosystem components)
• Traditional RDBMS (MS SQL Server, Oracle, MySQL, PostgreSQL)
• MPP (AWS Redshift, Teradata, Netezza)
• NoSQL (MongoDB, DynamoDB, Cassandra, Neo4J, Titan, Elasticsearch)
• Streaming Platform and Applications (Spark streaming, Kafka, Storm, etc.)
• Dev Ops (Github, Kubernetes Jenkins, Terraform)
• Data Modeling (Datavault, Star, Snowflake)

Ideally, you’ll also have

• Master’s degree in Business Administration (MBA) or Science (MS) preferred
• Prior consulting experience

What we offer you

Technology – Data and Decision Science – Data Engineering – Manager

In this role, you will design and build analytics solutions that deliver significant business value. You will collaborate with other data and analytics professionals, management, and stakeholders to ensure that business requirements are translated into effective technical solutions. Key responsibilities include:

• Understanding and analyzing business requirements to translate them into technical requirements.
• Designing, building, and operating scalable data architecture and modeling solutions.
• Staying up to date with the latest trends and emerging technologies to maintain a competitive edge.

Key Responsibilities:

As a Data Engineering Manager, you will play a crucial role in managing and delivering complex technical initiatives. Your time will be spent across various responsibilities, including:

• Leading workstream delivery and ensuring quality in all processes.
• Engaging with clients on a daily basis, actively participating in working sessions, and identifying opportunities for additional services.
• Implementing resource plans and budgets while managing engagement economics.

This role offers the opportunity to work in a dynamic environment where you will face challenges that require innovative solutions. You will learn and grow as you guide others and interpret internal and external issues to recommend quality solutions. Travel may be required regularly based on client needs.

Skills and attributes for success:

To thrive in this role, you should possess a blend of technical and interpersonal skills. The following attributes will make a significant impact:

• Lead the design and development of scalable data engineering solutions using Databricks on cloud platforms (e.g., AWS, Azure, GCP).
• Oversee the architecture of complex cloud analytics solutions, ensuring alignment with business objectives and best practices.
• Manage and mentor a team of data engineers, fostering a culture of innovation, collaboration, and continuous improvement.
• Collaborate with clients to understand their analytics needs and deliver tailored solutions that drive business value.
• Ensure the quality, integrity, and security of data throughout the data lifecycle, implementing best practices in data governance.
• Drive end-to-end data pipeline development, including data ingestion, transformation, and storage, leveraging Databricks and other cloud services.
• Communicate effectively with stakeholders, including technical and non-technical audiences, to convey complex data concepts and project progress.
• Manage client relationships and expectations, ensuring high levels of satisfaction and engagement.
• Stay abreast of the latest trends and technologies in data engineering, cloud computing, and analytics.
• Strong analytical and problem-solving abilities.
• Excellent communication skills, with the ability to convey complex information clearly.
• Proven experience in managing and delivering projects effectively.
• Ability to build and manage relationships with clients and stakeholders.

To qualify for the role, you must have:

• Bachelor’s degree in computer science, Engineering, or a related field required; Master’s degree preferred.
• Typically, no less than 4 - 6 years relevant experience in data engineering, with a focus on cloud data solutions and analytics.
• Proven expertise in Databricks and experience with Spark for big data processing.
• Strong background in data architecture and design, with experience in building complex cloud analytics solutions.
• Experience in leading and managing teams, with a focus on mentoring and developing talent.
• Strong programming skills in languages such as Python, Scala, or SQL.
• Excellent problem-solving skills and the ability to work independently and as part of a team.
• Strong communication and interpersonal skills, with a focus on client management.

Required Expertise for Managerial Role:

• Strategic Leadership: Ability to align data engineering initiatives with organizational goals and drive strategic vision.
• Project Management: Experience in managing multiple projects and teams, ensuring timely delivery and adherence to project scope.
• Stakeholder Engagement: Proficiency in engaging with various stakeholders, including executives, to understand their needs and present solutions effectively.
• Change Management: Skills in guiding clients through change processes related to data transformation and technology adoption.
• Risk Management: Ability to identify potential risks in data projects and develop mitigation strategies.
• Technical Leadership: Experience in leading technical discussions and making architectural decisions that impact project outcomes.
• Documentation and Reporting: Proficiency in creating comprehensive documentation and reports to communicate project progress and outcomes to clients.

Large-Scale Implementation Programs:

1. Enterprise Data Lake Implementation: Led the design and deployment of a cloud-based data lake solution for a Fortune 500 retail client, integrating data from multiple sources (e.g., ERPs, POS systems, e-commerce platforms) to enable advanced analytics and reporting capabilities.
2. Real-Time Analytics Platform: Managed the development of a real-time analytics platform using Databricks for a financial services organization, enabling real-time fraud detection and risk assessment through streaming data ingestion and processing.
3. Data Warehouse Modernization: Oversaw the modernization of a legacy data warehouse to a cloud-native architecture for a healthcare provider, implementing ETL processes with Databricks and improving data accessibility for analytics and reporting.

Ideally, you’ll also have:

• Experience with advanced data analytics tools and techniques.
• Familiarity with machine learning concepts and applications.
• Knowledge of industry trends and best practices in data engineering.
• Familiarity with cloud platforms (AWS, Azure, GCP) and their data services.
• Knowledge of data governance and compliance standards.
• Experience with machine learning frameworks and tools.