Associate Director, Data Platforms — Technical Lead

S&P Global, Inc.; Hyderabad; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

S&P Global Dow Jones Indices in Hyderabad seeks a senior data platform engineer to drive the transition of legacy pipelines to a lakehouse platform. You will partner with the Databricks team to implement repeatable ingestion, transformation, testing, deployment and monitoring patterns while enforcing security and governance.

You will apply Delta Lake, Apache Iceberg, and Unity Catalog concepts, design scalable pipelines, and support data mastering flows.

Qualifications

• 8+ years of experience in data engineering, data platforms, or cloud data architecture.
• Experience with Databricks-based platforms and migration to lakehouse patterns.
• Strong knowledge of AWS services and data governance concepts.

Responsibilities

• Lead data pipeline transitions and platform delivery with the Databricks team.
• Promote repeatable engineering patterns for ingestion, transformation, testing, deployment, and monitoring.
• Ensure secure, observable, and scalable lakehouse data pipelines using AWS and Delta Lake.

Skills

Data engineering

Cloud data architecture

Databricks

AWS services

Data pipelines

CI/CD

Security controls

LLM tooling

Tools

Amazon S3

AWS Glue

AWS Lambda

AWS Lake Formation

Amazon Kinesis

Databricks Unity Catalog

Delta Lake

Apache Iceberg

Job description

About the Role

Grade Level (for internal use): 12 Key Responsibilities Data Pipeline Transition and Platform Delivery Partner with the core Databricks team to plan and execute the transition of existing data pipelines to the target data platform. Drive the implementation of repeatable engineering patterns for ingestion, transformation, testing, deployment, and monitoring across onboarded datasets. Ensure pipelines are designed and managed in a way that supports long‑term platform consistency, reliability, observability, and ease of support. Guide the design and operation of cloud‑native data pipelines using AWS services such as: Amazon S3 for durable data lake storage AWS Glue for integration, cataloging, and processing AWS Lambda for event‑driven processing Amazon Kinesis for streaming use cases AWS Lake Formation for governed data lake controls Promote the use of AWS IAM, encryption, environment‑level controls, and platform guardrails to enforce secure access to platform resources and data products. Support practical application of lakehouse technologies and concepts such as Delta Lake, Apache Iceberg, Databricks Unity Catalog, metadata‑driven pipelines, and governed data access patterns. Data Onboarding and Asset‑Agnostic Enablement Define and operationalize onboarding patterns that support a broad range of data assets, domains, and source systems without requiring bespoke platform redesign for each use case. Work with platform, data engineering, architecture, governance, and business‑aligned teams to simplify and standardize how data is ingested, transformed, governed, and published to the enterprise platform. Create or contribute to reusable technical assets such as design patterns, reference implementations, onboarding templates, pipeline frameworks, technical documentation, and operational runbooks. Support asset‑agnostic onboarding by ensuring data pipelines are configurable, metadata‑driven, scalable, and aligned with enterprise data platform standards. Data Mastering Platform Integration Support integration of platform pipelines and datasets with the enterprise data mastering platform. Collaborate with upstream and downstream stakeholders to ensure mastered data can be consumed reliably through standardized interfaces and governed data flows. Help establish data quality controls, reconciliation processes, metadata alignment, and stewardship workflows required to support trusted mastered data in the platform. Contribute to issue resolution and continuous improvement related to mastering‑related ingestion and distribution workflows. Support data mastering capabilities aligned with platforms such as NeoXam DataHub, including: Data acquisition, Cleansing, Enrichment, Mastering, Reconciliation, Golden copy generation & Downstream distribution of trusted data products. Technical Leadership and Engineering Excellence Serve as a senior technical individual contributor for data platform engineering, providing expertise across pipeline migration, lakehouse architecture, AWS‑native data engineering, governance, and mastering integrations. Influence technical direction without direct people management responsibility. Contribute to architecture discussions, design reviews, implementation planning, code reviews, technical standards, and production readiness reviews. Translate broader architectural direction into actionable engineering patterns, implementation plans, and technical deliverables. Promote engineering best practices including: Version control, Automated testing, CI/CD, Release automation, Monitoring and alerting, Incident response, Documentation. Help establish cloud engineering standards for infrastructure automation, release management, and environment promotion using tools and services such as AWS CodePipeline, AWS CodeBuild, and infrastructure automation frameworks. Drive operational rigor across production data pipelines, including observability, logging, telemetry, support models, service ownership, and incident management. Collaboration, Governance, and Platform Standards Partner effectively with global platform, architecture, governance, security, Databricks‑aligned, and data mastering teams to ensure delivery aligns with enterprise standards. Act as a technical bridge between platform strategy and engineering execution. Support governance requirements through appropriate controls around: Data lineage Schema consistency Data quality Metadata Retention Access control Encryption Auditability Secure data distribution Ensure monitoring and operational health practices are in place using logging, alerting, telemetry, dashboards, and AWS‑native operational tooling where appropriate. Required Qualifications 8+ years of experience in data engineering, data platforms, cloud data architecture, or related engineering domains. Proven ability to drive technical initiatives and influence engineering outcomes in a complex, execution‑focused environment. Experience partnering with global or distributed teams to deliver platform and pipeline initiatives across time zones. Technical Expertise Strong hands‑on experience with modern data engineering and pipeline development, including batch and/or streaming data workflows. Experience working with Databricks‑based data platforms and supporting migration or transition of pipelines into a lakehouse‑oriented architecture. Strong familiarity with AWS cloud‑native data engineering, including services such as Amazon S3, AWS Glue, AWS Lambda, AWS Lake Formation, Amazon Kinesis, AWS IAM, and AWS‑native monitoring, logging, and security capabilities. Working knowledge of technologies and concepts such as Delta Lake, Apache Iceberg, Databricks Unity Catalog, metadata‑driven pipelines, data lake governance, lakehouse architecture, and catalog‑driven processing. Experience supporting data integration patterns involving mastering, MDM, reference data, market data, investment data, risk data, or trusted data distribution workflows. Solid understanding of data quality, schema management, lineage, metadata, access control, encryption, and operational support for production data pipelines. Experience with AWS IAM, data lake governance, policy‑based access controls, and secure platform operations. Familiarity with engineering best practices such as version control, automated testing, CI/CD, infrastructure automation, release management, and monitoring. Experience designing or implementing data platform observability and reliability practices, including alerting, monitoring, telemetry, operational dashboards, and production support procedures. AI Tooling and LLM‑Enabled Engineering Practical experience using AI tooling such as Claude, large language models, or similar AI‑assisted development platforms in an engineering context. Experience applying LLMs to data engineering or software engineering workflows, including code generation, refactoring, test creation, documentation, debugging, troubleshooting, and pipeline analysis. Ability to use AI‑assisted workflows to support Databricks, AWS data engineering, SQL, PySpark, pipeline migration, data quality analysis, and operational support activities. Ability to evaluate, validate, and refine AI‑generated code or recommendations before applying them to production‑grade engineering work. Collaboration and Execution Strong communication and stakeholder management skills, with the ability to work effectively across US‑based, offshore, and global teams. Ability to translate broader architectural direction into actionable technical deliverables, implementation plans, and reusable engineering patterns. Comfortable operating in a role that blends technical strategy, architectural influence, hands‑on engineering, and delivery enablement. Grade: 12 {9 to 13 years of experience} Location: Hyderabad Shift Time: 12 to 9 pm IST Working Model: twice a week / 9 days a month work from office

About S&P Global Dow Jones Indices

At S&P Global Dow Jones Indices, we provide iconic and innovative index solutions backed by unparalleled expertise across the asset‑class spectrum. By bringing transparency to the global capital markets, we empower investors everywhere to make decisions with conviction. We’re the largest global resource for index‑based concepts, data and research, and home to iconic financial market indicators, such as the S&P500® and the Dow Jones Industrial Average®. More assets are invested in products based upon our indices than any other index provider in the world. With over USD7.4 trillion in passively managed assets linked to our indices and over USD11.3 trillion benchmarked to our indices, our solutions are widely considered indispensable in tracking market performance, evaluating portfolios and developing investment strategies. S&P Dow Jones Indices is a division of S&P Global (NYSE:SPGI). S&P Global is the world’s foremost provider of credit ratings, benchmarks, analytics and workflow solutions in the global capital, commodity and automotive markets. With every one of our offerings, we help many of the world’s leading organizations navigate the economic landscape so they can plan for tomorrow, today. For more information, visit www.spglobal.com/spdji.

What’s In It For You?

Our Mission: Advancing Essential Intelligence. Our People: We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. Join us and help create the critical insights that truly make a difference.

Our Values: Integrity, Discovery, Partnership

Benefits

• Health & Wellness: Health care coverage designed for the mind and body.
• Flexible Downtime: Generous time off helps keep you energized for your time on.
• Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
• Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company‑matched student loan contribution, and financial wellness programs.
• Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best‑in class benefits for families.
• Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.
• For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries

Global Hiring and Opportunity at S&P Global

At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets.

Equal Opportunity Employer

Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. If you need an accommodation during the application process due to a disability, please send an email to:[e-mail] your request will be forwarded to the appropriate person.

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