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Walk-in || Gcp Data Engineer

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Summary

Senior Data Engineer role (6–10 yrs, walk-in) focused on end-to-end data platform migrations and building scalable data pipelines. Core stack includes GCP, BigQuery, Snowflake, SQL, Python, and Talend, with BI/reporting work in tools like Looker, Tableau, or Power BI.

Job Title: Senior Data Engineer The Opportunity... As a Senior Data Engineer, youll build software for end-to-end data platform migrations, including legacy system analysis, solution design, execution, validation, and decommissioning of obsolete platforms. How You'll Contribute...


Skills: GCP, BigQuery, SQL, Python, Data Engineering, Snowflake.

  • 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. What We're Looking For... •

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.
  • Must have experience with the following: o Working in a production data environment, with responsibility for building, maintaining, and supporting data pipelines and platforms; o 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 (Structured Query Language) 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 (Application Programming Interface) 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 (design, implementation, and support) using distributed systems, cloud platforms (one of the following: AWS (Amazon Web Services), GCP (Google Cloud Platform), Azure), data frameworks (one of the following: Spark, Kafka), and programing languages (one of the following: Python, C#, SQL), while prioritizing effectively and balancing speed, quality, and long-term goals; o Work independently while collaborating cross-functionally (engineering, analytics, product, and business), using tools such as Git, Jira, and BI platforms (one of the following: Tableau, Looker, Power BI), and proactively managing workstreams and contributing to team standards; and


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