Senior Data Engineer

Hello All,

• (we’re currently considering Mexico, Argentina, and other South or Latin American locations, but are open to your suggestions).

THE ROLE

• Lead activities that include data modeling (relational and dimensional), data lake & data warehouse development, data integration / ETL process development, OLAP semantic tier development, and support.
• Continuously deliver and improve prioritized enterprise data assets to support global analytics, reporting, and visualization solutions.
• Coordinate frequently with several enterprise support organizations and end users.
• Manage scheduling, support, tools, and maintenance of integration processes.
• Participate in Agile practices to elicit and refine requirements through an iterative process of planning, defining acceptance criteria, prioritizing, developing, and delivering enterprise data asset solutions.

YOU ARE

• An experienced engineer in designing and delivering data assets for corporate Business Intelligence & Reporting scenarios.
• Excited to shape new capability, position data assets for appropriate use cases, and influence project direction.
• A strong communicator with a technical vision for information management and analytics.
• Highly conversant in the culture and changing landscape of information technology.
• Curious and creative, always looking to deliver a superior product while working closely with a small scrum team.

YOU HAVE

• A Bachelor s Degree in Computer Science, Information Systems or a related field, or equivalent combination of education and experience.
• 5+ years of hands-on experience designing and developing data models, implementing data transformations, and managing production implementation of data assets for Reporting & Business Intelligence scenarios.
• 5+ years professional experience with one or more ETL tools such as Informatica, SQL Server Integration Services, Business Objects Data Services, or Spark.
• Experience in SQL and query optimization for data platforms such as Azure SQL DW/Synapse, Teradata, SAP HANA, Oracle, Redshift, Snowflake, or equivalent RDBMS. Experience with Azure Data Factory, Azure Data Lake, Azure Synapse, or Databricks is a bonus.
• Proficient in relational database concepts, including normalization, indexing, physical and logical modeling, SQL query creation, and performance tuning.
• Familiarity with the Kimball and/or Inmon methods of data warehousing, standards, and best practices, including star schema implementation and concepts like slowly changing and late arriving dimensions.
• Familiar with Data Lake and Spark concepts, and ideally experienced with Spark DataFrames and pySpark.