Data Engineer

Data Engineer

Overview:

The Data Engineer is responsible for developing data pipelines and/or data integrations of for Costcos enterprise certified data sets that are used for business critical data consumption use cases (i.e. Reporting, Data Science/Machine Learning, Data APIs, etc.). The Data Engineer will partner with product owners, data architects, and data platform teams to design, build, test, and automate data pipelines that are relied upon across the company as the single source of truth.

Responsibilities:

• Develops and operationalizes data pipelines to bring data into Costcos GCP landscape for the delivery of certified data sets
• Works in tandem with Data Architects, Data Stewards, and Data Quality Engineers to design data pipelines and recommends ongoing optimization of data storage, data ingestion, data quality and orchestration.
• Designs, develops, and implements ETL/ELT/CDC processes using Data Build Tool (DBT) and other native GCP Services (BigQuery Subscriptions, Dataproc, Dataflow, etc.)
• Uses GCP services such as BigQuery, AlloyDB, Spanner, Dataplex, Pub/Sub, Cloud Storage, etc. to improve and speed delivery of our data products and services.
• Identifies, designs, and implements internal process improvements: automating manual processes, optimizing pipeline delivery and support.
• Identifies ways to improve data reliability, efficiency, and quality of data management
• Participate in off hours 24/7 on call support on a rotational basis

Technical Skills:

• 5-8+ years experience engineering and operationalizing data pipelines with large and complex datasets.
• 5-8+ years hands-on experience with Data Build Tool (DBT), Dataflow & Dataproc (Spark)
• 5-8+ years experience working with BigQuery, Google Cloud Storage, AlloyDB and Spanner
• 5-8+ years experience with Data Pipeline, ETL/ELT, and Data Warehousing.
• Effective use of AI and/or LLMs to increase efficiency in deliverables.
• Extensive experience working with various data sources (DB2, SQL,Oracle, flat files (csv, delimited), APIs, XML, JSON).
• Experience implementing data integration techniques such as event/message based integration (Kafka, Google Pub/Sub).
• Advanced SQL skills; solid understanding of relational databases and business data; ability to write complex SQL queries against a variety of data sources.
• Strong understanding of database storage concepts (data lake, relational databases, NoSQL, Graph, data warehousing).
• Experience with Git / Azure DevOps / Jira.
• CDMP (Certified Data Management Professional) Certification.