Sr. Data Engineer, Analytics Engineering

Posted One Month Ago
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Mumbai, Maharashtra, IND
Hybrid
Senior level
Artificial Intelligence • Big Data • Enterprise Web • Fintech • Software • Financial Services
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The Role
Build and maintain enterprise data pipelines, ELT processes, data models, reporting structures, and analytics solutions. Cleanse, deduplicate, normalize, and govern data across warehouses and data lakes, including Snowflake. Develop dashboards and business intelligence models, ensure data quality and compliance, apply business logic, and collaborate with technical and non-technical stakeholders to deliver accurate insights and improve operational performance.
Summary Generated by Built In

Role: Sr. Data Engineer, Analytics Engineering

Location: Vashi, Navi Mumbai (4 days working from office)

Work Timings: Office work from 12:00pm to 5:00pm and then remote 7:30pm to 10:00pm

As a member of the Enterprise Data Platform team and Enterprise Technology organization within Technology & Engineering at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other’s words and actions, value constructive discussions and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us!

As a Senior Data Engineer on the Enterprise Data Platform team, you will be responsible for building data pipelines to ingest various source data from enterprise technologies and PitchBook Platform data, manipulating (cleanse, dedupe, normalize) data into well-constructed data models for data analysis, implementing business logic and standard calculations, governing (supporting, observing, documenting) the data, and making the data available to end consumers in the form of PitchBook data products built on top of our data warehouse/data lake (e.g. Snowflake). You’ll work with a range of data and reporting technologies (e.g. Python, Docker, Tableau, Power BI) to build upon a strong foundation of rigor, quantitative techniques, and efficient processing. You’ll join other Engineers and Analytics professionals as part of the team that develops data pipelines and insights for our internal stakeholders across Sales, Customer Success, Marketing, Research, Data Operations, Product, Finance, and Administration.

Your team will rely on you to build your skills in data techniques and analytics to deliver accurate, timely, accessible, and secure data & insights to users. You’ll collaborate closely and effectively with internal and external stakeholders of different roles and technical backgrounds, who have varying understanding of data engineering. You’ll have the opportunity and ability to impact many different areas of analytics and operational thinking across enterprise technology and product engineering.

You will exhibit a growth mindset, be willing to solicit feedback, engage others with empathy, and help create a culture of belonging, teamwork, and purpose. If you love building data-centric solutions, strive for excellence every day, are adaptable and focused, and believe work should be fun, come join us!

Primary Job Responsibilities

  • Apply unified data technologies to support advanced and automated business analytics

  • Design, develop, document, and maintain database and reporting structures used to compile insights

  • Define, develop, and review extract, load, and transform (ELT) processes and data modeling solutions

  • Consistently evolve data processes and techniques following industry best practices

  • Build data models to be used for reports and dashboards used to translate business data into insights, identify and prioritize operational improvement opportunities, and measure business KPIs against objectives

  • Contribute to the ongoing improvement of quality assurance standards and procedures

  • Support the vision and values of the company through role modeling and encouraging desired behaviors

  • Participate in various company initiatives and projects as requested

Skills and Qualifications

  • Bachelor's degree in a related field (Computer Science, Engineering, etc.)

  • 5+ years of experience in data engineering roles, including creating and maintaining data pipelines, data modeling, and data architecture

  • 5+ years of experience in advanced SQL, including expert-level skills in querying large datasets from multiple sources and developing automated reporting

  • 3+ years of experience in Python, with skills for diverse components of data pipelines, including scripting, data manipulation, custom extract, transform and loads, and statistical/regression analysis

  • Expertise in extract, transform, and load (ETL) and extract, load, transform (ELT) processes and pipelines, platforms (e.g. Airflow), and distributed messaging (e.g. Kafka)

  • Experience with tools that capture and control data modeling change management (e.g. SQLMesh)

  • Proficient in data storage solutions, data warehousing, and cloud-based data platforms (e.g. Snowflake)

  • Knowledge and applicable working experience establishing and ensuring data governance, data quality, and compliance standards

  • Exceptional problem-solving skills

  • Excellent communication and collaboration skills with the ability to engage with non-technical stakeholders

  • Experience working with enterprise technologies (CRM, ERP, Marketing Automation Platforms, Financial Systems, etc.) is a plus

Working Conditions       

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

Morningstar India is an equal opportunity employer

Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.

037_PitchBookDataInc PitchBook Data, Inc Legal Entity

Skills Required

  • Bachelor's degree in a related field such as Computer Science or Engineering
  • 5+ years of experience in data engineering, including data pipelines, data modeling, and data architecture
  • 5+ years of advanced SQL experience, including querying large datasets and developing automated reporting
  • 3+ years of Python experience involving scripting, data manipulation, custom ETL, and statistical or regression analysis
  • Expertise in ETL and ELT processes, pipelines, platforms such as Airflow, and distributed messaging such as Kafka
  • Experience with data modeling change-management tools such as SQLMesh
  • Proficiency in data storage solutions, data warehousing, and cloud-based data platforms such as Snowflake
  • Working experience establishing and ensuring data governance, data quality, and compliance standards
  • Exceptional problem-solving skills
  • Excellent communication and collaboration skills with non-technical stakeholders
  • Experience with enterprise technologies such as CRM, ERP, marketing automation, or financial systems

What the Team is Saying

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Morningstar Compensation & Benefits Highlights

  • Leave & Time Off Breadth — Time-off policies include flexible PTO and a paid sabbatical every four years, often highlighted as a standout perk. Feedback suggests this structure supports strong work–life balance and meaningful breaks.
  • Parental & Family Support — Policies advertise a global minimum of 16 weeks for primary caregivers, up to 8 weeks for secondary caregivers, and at least six weeks of paid caregiving leave. These offerings signal above-average support for family and caregiving needs.
  • Retirement Support — Retirement programs feature employer 401(k) contributions/matching, with some postings citing a 75% match on up to 7% of pay. Feedback suggests these offerings are a strong pillar of the package.

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The Company
HQ: Chicago, IL
11,500 Employees
Year Founded: 1984

What We Do

We are a global investment research and financial data company with 40-plus offices across North America, Europe, Australia, and Asia. Our products and services are used daily by individual investors, financial advisors, asset managers, retirement plan providers, and institutional investors. We provide data, research, and analysis across managed investment products, publicly listed companies, private capital markets, debt securities, and real-time global market data. The financial system can have real barriers—hidden information, friction that can slow decisions, and forces that can limit transparency and access. We work to remove them, bringing independent research, connected data, and investor-first tools to a system that needs more clarity. The people doing this work span research, technology, design, product, sales, and functional areas. We build many of our products in-house, so the work can connect directly to the tools investors use to make real financial decisions.

Why Work With Us

Morningstar’s missing is to empower investor success. We can only do that if our people feel empowered. That means finding people who think independently, bring a wide range of backgrounds with analytical rigor and genuine intellectual curiosity to the work.

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About our Teams

Morningstar Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Across most of our offices globally, employees work four days a week in the office and one day from home. We recognize that life doesn't always fit a fixed schedule and offer programs that can help provided increased workplace flexibility.

Typical time on-site: 4 days a week
Company Office Image
HQGlobal Headquarters
Ambler, Pennsylvania
Amsterdam - De Oliphant
Bucuresti, Bucuresti
Cape Town, Western Cape
Dubai
Edinburgh, Scotland
Frankfurt - Junghofstraße
Frankfurt - Neue Mainzer Straße
New Delhi
Hong Kong
London - Oliver's Yard
London - Saffron House
Madrid, Comunidad de Madrid
Milano, Lombardia
Mumbai - Platinum Park
Mumbai - Vishwaroop
New York - Broadway
New York - Park Ave
Paris, Ile-de-France
San Francisco, California
PitchBook US Headquarters
Sham Chun Hu, Guangdong
Singapore, Singapore
Stockholm - Birger Jarlsgatan
Sydney - International Tower
Timisoara, Timis
Tokyo - Minato-ku
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Toronto, ON
Zürich, Zurich
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