Data Engineer Manager
Contract Duration: 8+ Months (with potential extensions)
Location: Chicago, IL 60607 (Hybrid)
Employment Type: W2 Only (US Citizens, Green Card holders, and H4 EADs)
Job Description:
We are seeking a Senior Data Engineer Manager to lead and support our data engineering initiatives across cloud-based platforms, particularly Google Cloud Platform (GCP). This role requires strong hands-on experience in Python, PySpark, and big data technologies, along with a strategic mindset to drive data architecture and pipeline optimization for enterprise-scale systems.
You will play a critical role in designing, building, and managing scalable data solutions and leading a team of data engineers to deliver high-impact analytics and machine learning workloads. This hybrid position is based in Chicago, IL, and requires a blend of technical acumen, leadership skills, and cloud-native data engineering expertise.
Key Responsibilities:
- Lead the design and development of scalable, secure, and high-performance data pipelines using Python, PySpark, and GCP services.
- Architect batch and real-time data processing workflows leveraging tools such as Dataflow, Dataproc, Kafka, and Flink.
- Oversee end-to-end ETL/ELT processes, including ingestion, transformation, and loading of large datasets into BigQuery and other data warehouses.
- Collaborate with Data Scientists and ML Engineers to support AI/ML model deployment using AI Platform and AutoML.
- Manage a team of data engineers, providing technical guidance, code reviews, and performance feedback.
- Implement best practices for data modeling, data quality, governance, and data security across cloud environments.
- Build and maintain data visualization dashboards using Looker, Power BI, or other tools to provide actionable insights.
- Collaborate cross-functionally with business, product, and engineering teams to define and deliver on data strategy.
Required Skills & Qualifications:
- Proven experience as a Senior Data Engineer or Engineering Manager in cloud-native environments.
- Strong hands-on programming skills in Python and Spark/PySpark.
- Advanced knowledge of SQL for large-scale data manipulation and analytics.
- Expertise in Google Cloud Platform (GCP) fundamentals, including regions, zones, projects, IAM, and resource hierarchies.
- Experience with Dataflow, Dataproc, and BigQuery for building scalable pipelines and data lakes.
- Familiarity with AI Platform, AutoML, and ML Ops best practices.
- Strong background in ETL/ELT, data modeling, and data warehousing.
- Working experience with streaming platforms such as Kafka, Flink, or RabbitMQ.
- Proficiency in data visualization tools like Looker or Power BI.
- Excellent communication and leadership skills, with a proven track record of mentoring and managing teams.
Preferred Qualifications:
- GCP Certification is a plus.
