The Prime Video Finance Analytics team is looking for an experienced Data Engineer. The team is embedded within finance alongside content and business finance partners, we own the single-source-of-truth metrics layer that serves both finance and business leadership. Working across AWS technologies, you’ll deliver self-service analytics, infrastructure-as-code, and reliable ETL/ELT workflows. You’ll work closely with global business partners and technical teams on many non-standard and unique business problems and use creative problem solving to deliver data products that underpin Prime Video strategic decision making, from content selection to on‑platform customer experience.
Responsibilities
- Build and optimize data pipelines to ingest and transform data from various sources, including traditional ETL pipelines and event data streams.
- Utilize data from disparate sources to build meaningful datasets for analytics and reporting, focusing on consolidating data from various Prime Video systems.
- Implement big‑data technologies such as Redshift, EMR, Spark, SNS, SQS, Kinesis to optimize processing of large datasets.
- Develop and maintain the team’s data platform, including infrastructure‑as‑code using AWS CDK.
- Work closely with business stakeholders to understand their needs and translate them into technical solutions.
- Analyze business processes, logical data models, and relational database implementations.
- Write high‑performance SQL queries.
- Collaborate with software engineers to support the data needs of products.
Qualifications
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or Node.js.
- Experience with big data technologies such as Hadoop, Hive, Spark, EMR.
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets.
- Experience with data modeling, warehousing and building ETL pipelines.
- Knowledge of distributed systems as it pertains to data storage and computing.
- Knowledge of professional software engineering and best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence.
- Experience as a Data Engineer or in a similar role.
- Experience with SQL.
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, Firehose, Lambda, and IAM roles and permissions.
- Experience working on and delivering end-to-end projects independently.
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