Associate Director, Data Engineer

S&P Global; Gurugram District; On-site; INR 4,000,000 - 7,500,000; Full time

Job summary

S&P Global seeks an Associate Director, Data Engineer to design and build scalable ETL/ELT pipelines, lakehouse models, and Power BI data products for internal stakeholders. You will set engineering standards, mentor staff, and own data quality from ingestion to visualization in a large enterprise data platform.

You will work with Databricks, Microsoft Fabric, and Azure to deliver reliable, well-governed data assets and insightful reports across the organization, partnering with analytics and IT

Qualifications

• 8+ years in data engineering or BI related roles.
• Bachelor’s or Master’s in CS/Engineering/IS.
• Strong SQL and Python skills for data transformation.
• Experience with lakehouse architectures and Databricks.
• Familiarity with Azure cloud services and Power BI tooling.
• Knowledge of data governance, dictionaries and lineage.
• Ability to mentor and set best practices across teams.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines into the lakehouse.
• Develop data models and semantic layers for downstream reporting.
• Create and optimize Power BI dataflows and reports.
• Ensure data quality, testing, and documentation across datasets.
• Collaborate with stakeholders to translate data needs into technical solutions.
• Mentor junior engineers and drive architectural standards.

Skills

ETL/ELT pipelines

Lakehouse modelling

Python

SQL

Power BI

Databricks

Microsoft Fabric

Azure

Data governance

Architecture

Education

Bachelor's or Master's in CS/Engineering/IS

Tools

Databricks

Microsoft Fabric

Azure

Power BI

Job description

About the Role:

Grade Level (for internal use):

12

The Role: Associate Director, Data Engineer

The Team:

The Digital Technology Services (DTS) Business Intelligence team is responsible for providing DTS and the wider organization with data and insights through reporting on and around IT, Financials, and other corporate datasets. We are seeking an experienced and forward-thinking Senior Data Engineer to join the team. In this role, you will design and build the pipelines, lakehouse datasets, and Power BI data products that our internal customers rely on — from senior leadership to individual users — and set the engineering standards the team builds to. You will work across the full data-to-insight lifecycle, from extraction and data wrangling through to modelling, reporting, and ongoing support, using Databricks, Microsoft Fabric, Azure, and Power BI.

The Impact:

The Senior Data Engineer will be instrumental in how our organization understands and uses its corporate and technology data. By building reliable, well-modelled, and well-documented datasets and the reporting layer on top of them, this role will directly improve operational decision-making and reduce the time it takes to get from question to answer. The work will have downstream impact on our customers by ensuring our organization operates on reliable, high-integrity data — enabling faster insight, better governance, and a stronger data foundation across the enterprise.

What’sin it for you:

• Strong learning and growth opportunities: This role offers strong learning opportunities through close collaboration with experienced data professionals, along with hands‑on exposure to building enterprise data products end to end.
• Own high‑impact, enterprise‑wide data products: Take ownership of datasets and reports that underpin decision‑making across DTS and the wider organization — a role with visibility across technology leadership and business stakeholders.
• Work across the whole data lifecycle: Exciting and varied data, with each set presenting new and interesting challenges across extraction scripts, data wrangling and engineering, modelling, and reporting.
• Breadth of modern tooling: Gain hands‑on experience with Databricks, Microsoft Fabric, Azure, and Power BI in a live enterprise environment, and help shape how the team uses them.

Responsibilities:

• Design, build, and maintain scalable ETL/ELT pipelines that ingest data from diverse source systems into our lakehouse and warehouse.
• Apply data manipulations and transformations in SQL, Python, and Power BI (DAX / Power Query), and maintain and update the datasets our data products depend on.
• Design and evolve data models and gold‑tier datasets in Databricks and Microsoft Fabric for downstream reporting, consumption, and distribution.
• Leverage Azure cloud services for scalable data ingestion, transformation, storage, and processing.
• Implement automated job scheduling, monitoring, and observability, with self‑healing capabilities where possible.
• Own data quality in reporting and crafted data through automated testing, validation, reconciliation, and continuous improvement.
• Document data manipulations and transformations for the data dictionary, and uphold coding standards, code quality tooling, and automated test coverage across the team’s codebase.
• Work with the data produced at the data engineering layer to build useful, performant visualizations in Power BI.
• Build and maintain Power BI dataflows and semantic models, and set reports up to refresh reliably on an ongoing basis.
• Work with stakeholders to refine reports, and document each report and its inner workings so the team can assist in maintenance and improvements.
• Drive strategic initiatives that enable the team to deliver better products, faster and with world‑class support; champion support best practices and improve our users’ experience.
• Work closely with the scrum team, product owner, and other stakeholders to understand data requirements and translate them into technical solutions, collaborating with cross‑functional teams to design and implement data‑driven solutions.
• Serve as a senior technical contributor and mentor within the team, establishing best practices, coding standards, and architectural principles.
• Ultimately accountable for the quality and integrity of the data products and pipelines you own.

WhatWe’reLooking For:

Key qualifications:

• Experience: 8+ years in data engineering, business intelligence, or a related discipline, including time operating as a senior or lead technical contributor.
• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field.
• Data Engineering: Strong skills in ETL/ELT pipeline design, dimensional and lakehouse data modelling, and Python for data transformation.
• SQL: Advanced SQL for data manipulation, transformation, and performance tuning.
• Power BI: Proficiency in Power BI, DAX, Power Query, dataflows, and semantic model design, with strong analytical capability to read and interpret data and visualizations to draw insights.
• Lakehouse & Warehousing: Hands‑on experience with Databricks for scalable processing and Microsoft Fabric for data lakehouse architectures and data distribution; familiarity with comparable platforms (e.g. Snowflake, Dremio) is an advantage.
• Cloud Platforms: Proficiency with Azure cloud services for scalable data processing and storage.
• Testing & Quality: Experience with automated testing, code quality tools (e.g. Ruff), and caching solutions (e.g. Memcached).
• Data Governance: Experience with data governance, data security, and documentation practices, including data dictionaries and lineage.
• Forward‑Looking Architecture: Demonstrated ability to assess existing systems, identify gaps, and architect modern, scalable, future‑proof solutions.
• Flexibility: Open to working flexible hours as per business needs.

Preferred qualifications:

• Certifications in data architecture, engineering, or analytics (e.g. Microsoft Certified: Azure Data Engineer Associate, Databricks Certified Data Engineer, Google Cloud Professional Data Engineer).
• Understanding of the end‑to‑end data‑to‑insight lifecycle.
• Familiarity with machine learning and AI concepts and the data foundations they require.
• Experience with additional cloud computing platforms, including Amazon Web Services.
• Experience with Tableau or other visualization tools.

Soft Skills:

• Mentoring & Technical Leadership: Ability to guide, mentor, and raise the bar for a technical team while managing competing priorities.
• Expectation Management: Skilled at aligning stakeholders across business and technology on timelines, scope, and trade‑offs.
• Communication: Strong interpersonal skills, able to translate highly technical data and architecture concepts into clear, actionable narratives for a wide, non‑technical audience.
• Problem Solving: Strong analytical mindset with a pragmatic, data‑driven approach to diagnosing and resolving complex data quality challenges.
• Creativity & Continuous Improvement: Creativity in coming up with solutions around data and the end‑user experience, and a habit of staying current with trends and technologies in data tooling and engineering.

What’s In It For You?

Our Mission: