About the Role
We are looking for a Data Engineer to design, build, and maintain scalable data pipelines and platforms that power advanced analytics and AI solutions. You will work with modern Google Cloud data technologies to enable high-quality, reliable, and timely data for the business, with a focus on building new capabilities and ensuring platform reliability
Key Responsibilities
- Pipeline Development: Design, build, and maintain batch and streaming data pipelines using GCP services such as BigQuery, Dataflow, Dataproc, Composer, Dataform, and Cloud Functions.
- Data Modeling & Optimization: Implement and optimize data models in BigQuery to support analytics, BI reporting, and machine learning workloads.
- Data Integration: Connect and transform data from multiple sources, including APIs, databases, event streams, and flat files.
- Platform Reliability: Monitor and troubleshoot data pipelines, ensuring high availability, scalability, and cost efficiency.
- Governance & Quality: Implement data validation, quality checks, and security best practices to ensure trusted data.
- Collaboration: Work closely with analysts, BI developers (Tableau, MicroStrategy), and business teams to enable reporting and self-service analytics.
- Legacy Support (Light): Provide occasional support for legacy systems (Oracle, MicroStrategy) where needed, focusing on data extraction and gradual modernization.
Requirements
- Experience: 35 years of hands-on experience in data engineering, ETL/ELT development, or related roles.
- Technical Skills:
- Strong SQL and Python skills for data transformation and automation.
- Hands-on experience with GCP Data Stack (BigQuery, Dataflow, Composer, Dataproc, Dataform).
- Familiarity with orchestration workflows (Airflow/Composer) and CI/CD for data pipelines.
- Data Modeling: Understanding of relational, dimensional, and modern data modeling concepts, with an eye for performance optimization.
- Cloud Knowledge: Exposure to Azure Data Stack (Synapse, Data Factory, Databricks) is a plus.
- Mindset: Proactive, detail-oriented, and eager to work on building modern, scalable data solutions.
