10 days ago
Mexico City, MexicoEntry Level
Responsibilities
- Write and review high-quality code and SQL across the team.
- Drive engineering and operational projects for the Metrics and Data Platform team.
- Build extensible and intuitive datasets for internal customers.
- Implement operational improvements and enhancements to key business datasets.
- Identify risks, remove blockers, and ensure timely project delivery.
- Diagnose and root-cause bugs, bottlenecks, and inefficiencies.
- Collaborate with product managers and software engineers and managers.
- Communicate project updates clearly to technical and non-technical stakeholders and peers.
Requirements
- At least 1 year of data engineering experience.
- Experience with data modeling, data warehousing, and building ETL pipelines.
- Experience with one or more query languages such as SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, or Scala.
- Experience with one or more scripting languages such as Python or KornShell.
- Experience with a modern language such as Java, Python, C++, or C#, including object-oriented design.
- Fluent spoken, written, and reading English.
- Preferred experience with Hadoop, Hive, Spark, or EMR.
- Preferred experience with ETL tools such as Informatica, ODI, SSIS, BODI, or Datastage.
- Preferred experience with AWS technologies including Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions.
- Preferred experience with AWS QuickSight, Tableau, or open-source projects.
Categories
Data Engineering
About Amazon
Amazon builds and operates a global e-commerce marketplace, logistics network, and consumer devices, and provides cloud computing via AWS for businesses and developers. The company earns revenue from online retail, third‑party seller services, subscriptions like Prime, advertising, and AWS usage. Founded in 1994 and headquartered in Seattle, it is publicly traded on NASDAQ (AMZN) and serves customers in dozens of countries.