Data Engineer SQL

Job Summary

As a Senior Data Engineer, you'll build software for end-to-end data platform migrations, including legacy system analysis, solution design, execution, validation, and decommissioning of obsolete platforms.

Responsibilities

• Build software for end-to-end data platform migrations, including legacy system analysis, solution design, execution, validation, and decommissioning of obsolete platforms.
• Design and implement scalable, reliable software data pipelines supporting business analytics.
• Serve as a subject matter expert (SME) for software data flows, pipelines, and reporting logic.
• Proactively identify data dependencies, risks, and optimization opportunities across software systems.
• Partner with analytics, BI (Business Intelligence), and business stakeholders to deliver trusted, performant data solutions.
• Provide technical guidance to peers and help raise overall software engineering standards across the team.
• Take ownership of projects from design through production, including documentation and knowledge transfer.

Requirements

• Master's degree or foreign equivalent in Information Systems, Data Science, Data Analytics, Computer Science, Computer Engineering, or related field.
• Five (5) years of work experience in the position offered, as a Data Engineer, Software Developer, or related occupation.
• Working in a production data environment, with responsibility for building, maintaining, and supporting data pipelines and platforms;
• Leading cloud data migrations and platform modernization efforts, including planning, execution, and support of production systems during and after migration;
• BigQuery, Snowflake, and cloud-based data architectures, including designing, optimizing, and operating scalable data solutions in cloud environments;
• Migrating, supporting, and maintaining BI and reporting platforms such as Looker (Mode experience), including ensuring data accuracy, performance, and reliability of reporting;
• SQL and Python, with demonstrated ability to troubleshoot and resolve complex data quality, performance, and integration issues;
• Working with ETL/ELT (Extract, Transform, Load) tools (Talend) and modern data pipeline patterns, including data ingestion, transformation, orchestration, and monitoring in production environments;
• Building and managing marketing data integrations, including integrations with search engines, social media platforms, and other third-party marketing data sources;
• Internal and external API integrations, including ingesting, validating, and maintaining data from third-party and internal systems;
• Data warehousing concepts, including dimensional modeling, performance optimization, and cost aware design in cloud data platforms;
• Own and deliver complex technical solutions end-to-end using distributed systems, cloud platforms (AWS, GCP, or Azure), data frameworks (Spark, Kafka), and programming languages (Python, C#, SQL), while prioritizing speed, quality, and long-term goals;
• Work independently while collaborating cross-functionally (engineering, analytics, product, and business), using tools such as Git, Jira, and BI platforms (Tableau, Looker, Power BI), and proactively managing workstreams and contributing to team standards;
• Communicating complex technical concepts to diverse audiences, translating data architecture into clear documentation and diagrams using tools including Miro, Lucidchart, draw.io, Confluence, and Notion.

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