Senior Data Engineer

Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. We are in search of a highly motivated candidate to join our talented Team.

Location:

Seattle, WA

• AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure.
• We keep the cloud running by supporting all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on.
• We handle challenging problems with thousands of variables impacting the supply chain, and we’re looking for talented people who want to help.
• The Senior Data Engineer will join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles.
• They will collaborate with people across AWS to deliver the highest safety and security standards while providing seemingly infinite capacity at the lowest possible cost.
• The role provides an inclusive culture that welcomes bold ideas and empowers you to own them to completion.
• The Senior Data Engineer will help grow our Data Lake and Data Warehouse Systems built using a serverless architecture with 100% native AWS components such as Redshift Spectrum, Athena, S3, Lambda, Glue, EMR, Kinesis, SNS, Cloud Watch, and more.
• Our Data Lake drives multi‑billion dollar decisions regularly and we aim to improve lake filling speed, reduce human intervention, and democratize data.
• Data Engineers build ETL and analytics solutions for internal customers to answer data questions, drive critical business improvements, and apply best practices in software engineering, data management, data storage, data compute, and distributed systems.

• Develop and maintain automated ETL pipelines (with monitoring) using scripting languages such as Python, Spark, SQL and AWS services such as S3, Glue, Lambda, SNS, SQS, KMS.
• Implement and support reporting and analytics infrastructure for internal business customers.
• Develop and maintain data security and permissions solutions for enterprise‑scale data warehouse and data lake implementations including data encryption and database user access controls and logging.
• Develop data objects for business analytics using data modeling techniques.
• Develop and optimize data warehouse and data lake tables using best practices for DDL, physical and logical tables, data partitioning, compression, and parallelization.
• Develop and maintain data warehouse and data lake metadata, data catalog, and user documentation for internal business customers.
• Work with internal business customers and software development teams to gather and document requirements for data publishing and consumption via data warehouse, data lake, and analytics solutions.

• Fixing automation issues daily
• Ensuring quality of work and fixes

• 5 years of data engineering experience
• Experience with data modeling, warehousing, and building ETL pipelines
• Experience with SQL
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS