Data Engineer I, Business Data Technologies

Overview

Data Engineer I, Business Data Technologies (BDT) builds and manages data infrastructure to help Amazon teams produce, store, catalog, secure, move, and analyze data at massive scale. BDT combines standard AWS tooling, open-source products, and custom services to free teams from the complexities of operating at Amazon scale, enabling them to focus on extracting value from their data for customers and teams. We own one of the biggest data lakes for Amazon where thousands of teams can search, share, and store exabytes of data in a secure and seamless way; our solutions support millions of workloads daily with emphasis on compliance, security, integrity, and cost efficiency.

Responsibilities

• Be hands-on with ETL to build data pipelines to support automated reporting.
• Interface with other technology teams to extract, transform, and load data from a wide variety of data sources.
• Implement data structures using best practices in data modeling, ETL/ELT processes, and SQL, Redshift.
• Model data and metadata for ad-hoc and pre-built reporting.
• Interface with business customers, gathering requirements and delivering complete reporting solutions.
• Build robust and scalable data integration (ETL) pipelines using SQL, Python and Spark.
• Build and deliver high quality data sets to support business analysts, data scientists, and customer reporting needs.
• Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.
• Participate in strategic and tactical planning discussions.
• A day in the life: collaborate with cross-functional partners to translate raw data into actionable insights for stakeholders and empower data-driven decisions. Design and build data pipelines, ensure data integrity with quality checks, and automate processing tasks to streamline workflows.

Qualifications

BASIC QUALIFICATIONS

• 1+ years of data engineering experience.
• Experience with SQL.
• Experience with data modeling, warehousing and building ETL pipelines.
• Experience with one or more query languages (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala).
• Experience with one or more scripting languages (e.g., Python, KornShell).

PREFERRED QUALIFICATIONS

• Experience with big data technologies such as Hadoop, Hive, Spark, EMR.
• Experience with ETL tools like Informatica, ODI, SSIS, BODI, Datastage, etc.
• Knowledge of cloud services such as AWS or equivalent.

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