Senior Data Engineer, Amazon Logistics

Amazon Logistics is seeking a passionate Senior Data Engineer to join their team in revolutionizing how millions of products are delivered to customers worldwide. This role sits at the intersection of one of the world's most complex logistics operations and cutting-edge data engineering.

The position offers an opportunity to work with one of the world's largest data warehouse environments, where you'll be instrumental in designing and implementing solutions that directly impact Amazon's delivery efficiency and cost-effectiveness. You'll be working with emerging AWS technologies like Redshift, Kinesis, Lambda, and EMR to build scalable data infrastructure from the ground up.

As a Senior Data Engineer, you'll collaborate with scientists, global supply chain teams, and transportation experts to develop innovative solutions for complex cost and cycle time optimization problems. The role requires someone who combines deep technical expertise in data engineering with strong business acumen, capable of translating business requirements into robust data solutions.

Key responsibilities include owning the data engineering space for Amazon logistics, building real-time and batch data pipelines, and leading the adoption of next-generation technologies like AWS BedRock and Lake Formation. You'll also play a crucial role in mentoring junior engineers and establishing data quality standards for the organization.

The position offers competitive compensation ranging from $139,100 to $240,500 based on location and experience, along with comprehensive benefits. This is an excellent opportunity for someone who loves working with data at scale and wants to make a significant impact on one of the world's largest logistics operations.

The ideal candidate will bring 5+ years of data engineering experience, strong SQL skills, and expertise in modern programming languages like Python or Java. Experience with big data technologies such as Hadoop, Hive, and Spark is highly valued. This role offers clear growth potential, with opportunities to transition into people management leading a team of 4-5 data engineers.