Data Engineer Level 3

For over half a decade, Hudson Manpower has been a trusted partner in delivering specialized talent and technology solutions across IT, Energy, and Engineering industries worldwide. We work closely with startups, mid-sized firms, and Fortune 500 clients to support their digital transformation journeys. Our teams are empowered to bring fresh ideas, shape innovative solutions, and drive meaningful impact for our clients. If you're looking to grow in an environment where your expertise is valued and your voice matters, then Hudson Manpower is the place for you. Join us and collaborate with forward thinking professionals who are passionate about building the future of work.

Core Responsibilities

Design, develop, and optimize scalable ELT / ETL data pipelines leveraging Azure Synapse, Databricks, and PySpark .

Build and manage data lake house architectures for high-volume eCommerce, marketing, and behavioral datasets.

Model complex event-level data (clickstream, transactions, campaign interactions) to power dashboards, A / B testing, ML models , and marketing activation .

Implement Delta Lake optimization and Databricks Workflows for performance and reliability.

Partner with architects and business analysts to deliver reusable, high-quality data models for BI and self-service analytics.

Ensure data lineage, governance, and compliance using Unity Catalog and tools like Alation .

Collaborate with data scientists to productionize and operationalize datasets for ML and predictive analytics.

Validate and reconcile behavioral data with Adobe Analytics and Customer Journey Analytics (CJA) to ensure accuracy.

Maintain semantic models for Power BI dashboards, supporting self-service and advanced analytical insights.

Actively participate in Agile delivery : sprint planning, backlog refinement, technical documentation, and code reviews.

Required Qualifications

7+ years of experience in data engineering, data architecture, or similar roles.

Expertise in Databricks , Azure Synapse , Delta Lake , and Spark-based data processing .

Strong SQL proficiency for data transformation and performance tuning .

Deep experience with modern data architectures (Lakehouse, ELT, streaming).

Proven track record in handling behavioral / eCommerce datasets and analytics use cases.

Hands-on experience with Unity Catalog and metadata governance tools (e.g., Alation).

Experience with Adobe Analytics / CJA data validation preferred.

Familiarity with Power BI , Python , and data orchestration tools (ADF, Airflow).

Strong communication skills with the ability to bridge business needs and engineering solutions.

Experience in Agile environments with proven leadership in technical delivery.