Data Engineering Manager

Key Skills

Java Programming, Python Programming, SQL Server, Apache Hadoop, Scala Programming, Apache Hive, SPARK Programming, SSIS, Data pipelines

Job Description

GoDaddy is empowering everyday entrepreneurs around the world by providing all of the help and tools to succeed online. With 20 million customers worldwide, GoDaddy is the place people come to name their idea, build a professional website, attract customers and manage their work. Our mission is to give our customers the tools, insights and the people to transform their ideas and personal initiative into success. To learn more about the company visit www.GoDaddy.com.

Location:

What you'll get to do...

We are part of GoDaddy’s Data and Analytics team. Our team is globally distributed and are focused on providing data solutions to various internal analytics teams.

Our ideal candidate thrives in a fast-paced environment, enjoys the challenge of highly complex business contexts (that are typically being defined in real-time), and, above all, is a passionate about data and analytics. In this role you will be part of a team of engineers to create a platform to drive deep insights around GoDaddy’s business to help our customers succeed in theirs.

• Lead a globally distributed team of data engineers (50% leading and 50% hands-on design and development of solutions)
• Interface with our Business Analytics team, gathering requirements and delivering complete BI solutions.
• Model data and metadata to support ad-hoc and pre-built reporting.
• Own the design, development, and maintenance of datasets our BA teams will use to drive key business decisions.
• Adopt and define the standards and best practices in data engineering including data integrity, validation, reliability, and documentation.
• Tune and ensure query performance using profiling tools and SQL.
• Analyze and solve problems at their root, stepping back to understand the broader context.
• Learn and understand a broad range of GoDaddy’s data resources and know when, how, and which to use and which not to use.
• Keep up to date with advances in big data technologies and run pilots to design the data architecture to scale with the increased data volume using AWS.
• Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for datasets.
• Triage many possible courses of action in a high-ambiguity environment, making use of both quantitative analysis and business judgment.

Your experience should include...

• Bachelor’s degree in CS or related technical field.
• 10+ years of experience in data modeling, ETL/ELT development, and Data Warehousing.
• 3+ years of experience in Cloud data engineering (S3, RDS, Redshift & EMR)
• 1+ years of experience in leading the teams
• Experience working with Big Data solutions (Hadoop, Hive, Spark).
• Data pipeline performance tuning.
• Strong organizational and multitasking skills with ability to balance competing priorities.
• Experience in programming using Python, Java or Scala
• Excellent communication (verbal and written) and interpersonal skills and an ability to effectively communicate with both business and technical teams.
• An ability to work in a fast-paced environment where continuous innovation is occurring and ambiguity is the norm.

You might also have...

• Experience in MS SQL Server (SQL server, Stored procs, SSIS) is a plus