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Data Engineer

Remote, Remote
Data Engineer
6+ Month CTH
Remote
 

Data Engineering is the engine that powers our data obsessed eCommerce enterprise. We move fast, iterating quickly on big business problems. We work smart, applying technology to unlock insights and provide outsized value to our customers. We swing big, knowing our customers won't benefit from micro optimizations. Leveraging the largest data set for products sold in the Home space, this team treats data as an asset and determines how to maximize its business value and extend our competitive advantage.

 

What You’ll Do

Own an entire key area of data within Client from generation to consumption, such as a trillion rows clickstream dataset or millions of orders and related events generated across our supply chain source systems

Collaborate with your stakeholders and other business analytics team leaders to define and develop the data architecture and data solution roadmap for the functional areas you support.

Act as a subject matter expert to leadership for technical guidance, solution design and best practices.

Design and implement big data architecture, data pipelines, reporting, dashboarding, data exploration, processes and quality controls to enable self-service Business Intelligence and advanced analytics

Keep current on big data and data visualization technology trends, evaluate, work on proof-of-concept and make recommendations on the technologies based on their merit.

Manage and mentor associates; ensure the team is being challenged, exposed to new opportunities, and learning, while still being able to deliver on ambitious goals.

Develop a technical center of excellence within the analytics organization through training, mentorship, and process innovation.

Build, lead, and mentor a team of highly talented data professionals working with petabyte scale datasets and rigorous SLAs

Who You Are

A true expert on big data, comfortable working with datasets of varying latencies and size and disparate platforms

Excited about unlocking the valuable data hidden in inaccessible raw tables and logs

Attentive to detail and with a relentless focus on accuracy

Excited to collaborate with partners in business reporting and engineering to determine the source of truth of key business metrics

  Excellent communication and presentation skills, strong business acumen, critical thinking, and ability to work cross functionally through collaboration with engineering and business partners.

Demonstrated success working with stakeholders and implementing end-to-end data solutions including data model, data pipelines and Business Intelligence products to solve complex business requirements.

 

What You Have

5+ years of experience in designing and implementing large-scale global Data warehouse architectures, OLAP technologies, Star-schema, Snowflake schema and Aggregation Techniques.

3+ years of hands-on experience of Data Lake/Hadoop platform and performance tuning Hadoop/Spark implementations.

Experienced developing in cloud platforms such as Google Cloud Platform (preferred), AWS, Azure, or Snowflake at scale.

Experience with one or more relevant tools (Kafka, Avro, Sqoop, Flume, Parquet) and SQL-on-Hadoop technology (Hive, Spark SQL, Presto)

Experience with real-time data streaming tools like Kafka, Beam, Flink, Kinesis, Apache Storm or any similar tools.

Experience in development of custom built BI and big data reporting solutions using tools like DataStudio, Looker, Tableau, AtScale, PowerBI, Qlik, or any similar tools.

Experience architecting database management systems (such as Oracle, MySQL, PostgreSQL, MS SQL Server) and analytical technologies in the industry including MPP (Vertica, Teradata, Redshift) and NoSQL databases (such as Cassandra, MongoDB, Redis, Aerospike). Prior experience with databases 100TB+ highly desired.

3+ years of programming experience with at least one language such as Python, Java, Scala, C++ or other modern OOP programing language

Advanced SQL proficiency highly desired.

Experience with code management tools (e.g. Git, SVN) and DevOps tools (e.g. Docker, Bamboo, Jenkins)

Bachelors or Masters in Computer Science, Computer Engineering, Analytics, Mathematics, Statistics, Information Systems, Economics, Management or other quantitative discipline fields with strong academic record.

 

What we’d love to see (but isn’t required)

 Supply Chain or Ecommerce analytics experience a strong plus

Experience in designing data engineering solutions using open source and proprietary cloud data pipeline tools such as Airflow, Glue and Dataflow

Prior experience in data science or closely related quantitative field

Hands-on experience building and deploying production ML models at scale

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