Senior Data Engineer

Employment Type: [Not Specified] Location Type: Hybrid (India) Salary: [Not Specified]

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About YipitData:

YipitData is the leading market research and analytics firm for the disruptive economy and recently raised up to $475M from The Carlyle Group at a valuation over $1B. We analyze billions of alternative data points every day to provide accurate, detailed insights on ridesharing, e-commerce marketplaces, payments, and more. Our on-demand insights team uses proprietary technology to identify, license, clean, and analyze the data many of the world’s largest investment funds and corporations depend on.

For three years and counting, we have been recognized as one of Inc’s Best Workplaces. We are a fast-growing technology company backed by The Carlyle Group and Norwest Venture Partners. Our offices are located in NYC, Austin, Miami, Denver, Mountain View, Seattle, Hong Kong, Shanghai, Beijing, Guangzhou, and Singapore. We cultivate a people-centric culture focused on mastery, ownership, and transparency.

Why You Should Apply NOW:

• You’ll be working with many strategic engineering leaders within the company.
• You’ll report directly to the Director of Data Engineering.
• You will help build out our Data Engineering team presence in India.
• You will work with a Global team.
• You’ll be challenged with a lot of big data problems.

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About The Role:

We are seeking a highly skilled Senior Data Engineer to join our dynamic Data Engineering team. The ideal candidate possesses 6-8 years of data engineering experience. An excellent candidate should have a solid understanding of Spark and SQL, and have data pipeline experience. Hired individuals will play a crucial role in helping to build out our data engineering team to support our strategic pipelines and optimize for reliability, efficiency, and performance.

Additionally, Data Engineering serves as the gold standard for all other YipitData analyst teams, building and maintaining the core pipelines and tooling that power our products. This high-impact, high-visibility team is instrumental to the success of our rapidly growing business. This is a unique opportunity to be the first hire in this team, with the potential to build and lead the team as their responsibilities expand.

This is a hybrid opportunity based in India.

• During training and onboarding, we will expect several hours of overlap with US working hours.
• Afterward, standard IST working hours are permitted with the exception of 1-2 days per week, when you will join meetings with the US team.

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As Our Senior Data Engineer You Will:

• Report directly to the Senior Manager of Data Engineering, who will provide significant, hands-on training on cutting-edge data tools and techniques.
• Build and maintain end-to-end data pipelines.
• Help with setting best practices for our data modeling and pipeline builds.
• Create documentation, architecture diagrams, and other training materials.
• Become an expert at solving complex data pipeline issues using PySpark and SQL.
• Collaborate with stakeholders to incorporate business logic into our central pipelines.
• Deeply learn Databricks, Spark, and other ETL toolings developed internally.

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You Are Likely To Succeed If:

• You hold a Bachelor’s or Master’s degree in Computer Science, STEM, or a related technical discipline.
• You have 6+ years of experience as a Data Engineer or in other technical functions.
• You are excited about solving data challenges and learning new skills.
• You have a great understanding of working with data or building data pipelines.
• You are comfortable working with large-scale datasets using PySpark, Delta, and Databricks.
• You understand business needs and the rationale behind data transformations to ensure alignment with organizational goals and data strategy.
• You are eager to constantly learn new technologies.
• You are a self-starter who enjoys working collaboratively with stakeholders.
• You have exceptional verbal and written communication skills.

Nice to have:

• Experience with Airflow, dbt, Snowflake, or equivalent.

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What We Offer:

[Not Specified]