Job at a glance
Our client, is seeking an experienced, highly analytical Senior Data Engineer to join their rapidly growing Analytics team. In this high-impact role, you will design, build, and optimize scalable data pipelines to organize, transform, and manage billions of rows of data for advanced analytics and strategic decision-making. Leveraging Google BigQuery, Python, and deep domain expertise, you will translate complex business requirements into high-performance transformations, building clean tables and views for executive dashboards and self-service analytics.
Operating in an empowering, data-driven environment, you will collaborate closely with business leaders and cross-functional technology squads to build automated, reliable data solutions that power customer experience initiatives and drive business value. Duration: 4-Month Contract (with high potential for extension) Advantages Massive Data Scale Scope: Direct the design and optimization of enterprise-grade pipelines organizing, transforming, and optimizing billions of rows of data.
Modern GCP Cloud Ecosystem: Work extensively with top-tier cloud data technologies, including Google BigQuery, GCP Dataflow, Pub/Sub, PySpark, Airflow, and Vertex AI. High-Visibility Business Impact: Deliver analytics-ready tables and self-service data models that directly inform strategic business decisions and executive dashboards. Empowering & Collaborative Environment: Join a highly skilled, innovative analytics group focused on creative problem-solving and modern data engineering practices.
Responsibilities Pipeline Engineering & Architecture: Design, develop, and maintain robust, scalable data pipelines and automated ETL/ELT processes for large-scale structured and unstructured datasets. BigQuery & Analytics Optimization: Leverage Google BigQuery, Python, GBQ stored procedures, and advanced query optimization to build reliable data assets, aggregated scorecards, and dashboard tables.
Requirements Translation: Collaborate with business teams, data analysts, and cross-functional stakeholders to translate complex business needs into clear, efficient data transformations. Data Quality & Governance: Implement automated data validation checks, monitoring, and governance frameworks to guarantee accuracy, performance, and data integrity across massive datasets. Process Automation & Analytics Support: Automate manual data processes, prepare ad-hoc data extractions, and derive actionable insights from complex data streams (including clickstream data).
Technical Communication: Effectively articulate complex technical concepts and pipeline designs to business-oriented stakeholders, ensuring strategic alignment. Qualifications Professional Experience: 7+ years of progressive experience in data engineering, big data platform management, or a closely related field. GCP & BigQuery Mastery: Hands-on experience working within the Google Cloud Platform (GCP) ecosystem, with deep expertise in Google BigQuery, BigQuery stored procedures, and GCP data services.
Programming & SQL Depth: Advanced proficiency in Python and expert-level SQL skills with a track record of optimizing complex queries and building stored procedures. Big Data & Orchestration: Proven experience with big data frameworks, workflow orchestration, and data warehousing platforms (PySpark, Apache Airflow, GCP Dataflow, Pub/Sub, Snowflake, or Redshift). Education: Bachelor’s degree in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or a related quantitative discipline.
Preferred Assets & Certifications Professional certifications such as Google Professional Data Engineer, AWS Certified Data Analytics / Big Data Specialty, or Microsoft Certified: Azure Data Engineer Associate. Familiarity with advanced analytics tools and modern data lake formats (Vertex AI, Apache Iceberg, StarRocks, Applied AI/ML concepts). Exposure to clickstream data processing and ITIL frameworks (ITIL Foundation).
Summary If you are a tech-savvy Seni