Software Engineer I - ETL Engineering

US Remote

Applications have closed

About Us

YipitData is the leading market research firm for the disruptive economy and recently raised $475M from The Carlyle Group at a valuation of over $1B.

We analyze billions of 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.

We are one of Inc’s Best Workplaces - a fast-growing technology company with offices located in NYC (where we are based in), Hong Kong, and Shanghai, backed by Norwest Venture Partners and The Carlyle Group with a strong culture focused on mastery, ownership, and transparency.

About the Data Engineering Department:

Data Engineering’s mission is to create the best-in-class data analytics platform to support YipitData’s current and future data needs. Our self-service data platform empowers our Investor and Corporate product teams to analyze billions of data points every day to provide accurate, granular insights to their clients.

The Data Engineering Department is composed of 4 teams, including Data Infrastructure, Data Platform Engineering, ETL Engineering, and Analytics Engineering (~15 engineers). We offer a highly collaborative work environment where Data Engineering teams meet regularly to review architectures and strategies to empower a technical audience of data users at the company. Each team has a high degree of ownership and opportunity to work with state of the art tools in the data industry to reach their objectives. We offer the flexibility to switch teams based on your skills and career aspirations, a career ladder with growth opportunities, good work/life balance, and we have a very high employee retention rate.

About The Role:

We are looking for a Software Engineer I to join our Data Engineering ETL team.

ETL Engineering team’s mission is to create the best-in-class tooling to build highly performant and reliable data pipelines. We build and maintain the most critical data pipelines at YipitData, including processing high volumes of 1st and 3rd party datasets that fuel all of our data products. We also set the gold standard for how other YipitData analyst teams build their own data pipelines, and provide training and support for 250+ analysts. The ETL team is a high-impact, high-visibility team that will be crucial to the success of our growing data feed business. We collaborate with many different stakeholders across our Investor and Corporate business units.

This is a remote-friendly opportunity that can be based in NYC, where our headquarters is located, or anywhere in the US (we expect Eastern Time working hours).

As a Software Engineer I you will:

  • Build, manage, and support different internal data pipelines
  • Collaborate with stakeholders to enforce best practices.
  • Build tooling to enable product teams to build their pipelines.
  • Collaborate with engineers and business stakeholders to come up with the best solution for creating pipelines.
  • Write documentations and help shape the future of the ETL team.
  • Responsible for ingesting Edison data sources

On a given day, you might:

  • Work with our stakeholders to build an efficient pipeline
  • Help create documentation for our internal tooling.
  • Work with Data Platform Engineers to experiment with new Databricks features
  • Help build our internal toolkit that’ll be used by stakeholders
  • Monitor different pipelines for optimization opportunities

As long as you've worked with modern data tools, we're positive that you will learn and understand our technology stack:

  • AWS: S3, CloudFormation (CDK) and many more
  • Databricks, Fivetran, Snowflake
  • Python, PySpark, Spark, SQL, Git
  • For business tools we use: GSuite, Slack, Asana, Zoom

You Are Likely to Succeed If:

  • Bachelor's or Master's degree in Computer Science, STEM or related technical discipline (such as bootcamp), or equivalent experience 
  • 1-3 years of experience as a Software Engineer, Data Engineer, or Data Analyst 
  • You are comfortable working with large-scale datasets using PySpark or Pandas
  • You are a self-starter who enjoys working collaboratively with stakeholders
  • You have some understanding of building data pipelines
  • You are excited about solving data challenges and learning new skills
  • You have strong verbal and written communication skills
  • Nice to have: experience with SQL, Databricks, Pyspark/Pandas, Python

What We Offer:

  • Our compensation package includes equity and a highly competitive salary.
  • We care about your personal life. We offer flexible work hours, open vacation policy, a generous 401K match, parental leave, team events, wellness budget, learning reimbursement, and more.
  • Your growth at YipitData is determined by the impact that you are making, not by tenure, unnecessary facetime, or office politics. Everyone at YipitData is empowered to learn, self-improve, and master their skills in an environment focused on ownership, respect, and trust.
  • To learn more about our culture and values, check out our Glassdoor page.

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity employer.

 

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Architecture Asana AWS CloudFormation Computer Science Data Analytics Databricks Data pipelines E-commerce Engineering ETL FiveTran Git Market research Pandas Pipelines PySpark Python Research Snowflake Spark SQL STEM

Perks/benefits: 401(k) matching Career development Competitive pay Equity Flex hours Flex vacation Parental leave Startup environment Team events Wellness

Regions: Remote/Anywhere North America
Country: United States
Job stats:  29  7  0
Category: Engineering Jobs

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