Senior Data Engineer

At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.

This is a hybrid position. You ll divide your time between working remotely from your home and an office, so you should live within commuting distance. Hybrid teams may work in-office as much as a few times a week or as little as once a month or quarter, as decided by leadership. The hiring manager can share more about what hybrid work might look like for this team.

Join our Team

Data is the most valuable asset in GoDaddy, and the Corporate Technology team is redefining the way data is accessible to our employees - to help inform critical decision making and action from our workforce.

Our Data Engineers not only understand how technology works, but how that technology intersects with the people who count on it every day. So, if you re interested in a career crafting data-driven products and making an impact through improved data and insights, look no further!

What youll get to do...

• Develop full-stack high-quality batch and streaming big Data Products - data modeling, pipeline for data & AI/ML model inferencing as well as data visualization
• Collaborate with our Data Consumers across a variety of corporate functions - primarily HR, but up to and including Legal, Technology and Finance, to gather and enrich requirements, and deliver complete data solutions
• Own the development, and maintenance of datasets that drive key business decisions, and keep up to date with advances in big data tech stack and run pilots to develop the data architecture to scale with the increased data volume using cloud services
• Adopt, define and refine the standards and best practices in data engineering including data integrity, performance optimization, validation, reliability, and documentation
• Triage many possible courses of action in a highly ambiguous environment, making use of both quantitative analysis and business judgment, while architecting and implementing data lake solutions, addressing common data concerns, such as data quality, data governance
• Play a key role in integrating new, 1st party and 3rd party (SaaS) data sources into our data & analytical ecosystem over the AWS cloud

Your experience should include...

• 7+ years of experience in data engineering.
• Track record of delivering reliable data pipelines with proven test infrastructure, CICD, data quality checks, monitoring, and alerting and creating a data platform strategy.
• Extensive experience with data visualization tools, particularly Amazon QuickSight
• Familiarity with SQL and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Cassandra).
• Familiarity with DevOps practices and CI/CD pipelines (AWS DevOps, GitHub Actions/Jenkins)
• Experience working with Big-Data technologies (Spark, Kafka, Kinesis)

You might also have...

• Proficiency in data modeling and design, with metadata management like Glue Catalog
• Experience in programming using Python, Java/Scala
• Experience with data orchestration tools (Airflow, Oozie, Step Functions)
• Experience in data quality tools like Deque or Great Expectations
• Knowledge of standard ML techniques (e.g. Regression, Classification, Anomaly, Forecasting) by using standard ML Libraries part of Spark, Python, etc. is desirable

Weve got your back... We offer a range of total rewards that may include paid time off, retirement savings (e.g., 401k, pension schemes), bonus/incentive eligibility, equity grants, participation in our employee stock purchase plan, competitive health benefits, and other family-friendly benefits including parental leave. GoDaddy s benefits vary based on individual role and location and can be reviewed in more detail during the interview process.

We also embrace our diverse culture and offer a range of Employee Resource Groups ( Culture ). Have a side hustleNo problem. We love entrepreneurs! Most importantly, come as you are and make your own way.