Data Engineer

-Join a well known brand within Corporate Banking

-Excellent career development opportunities

-Great work environment

Our client is a trusted partner in strategic talent acquisition and staffing. Since 2011, our client has developed strong alliances with global IT and non-IT firms, becoming a cornerstone in the industry.

The Job

Key Responsibilities

Lead the design and development of robust ETL workflows using Informatica/ PowerCenter/IICS/IDMC.

Architect and implement scalable data sourcing strategies from diverse systems (on-prem, cloud, APIs).

Ensure data quality, lineage, and governance across ingestion pipelines.

Design logical and physical data models aligned with business domains and data product principles.

Contribute to the architecture of enterprise data lakes and data platforms.

Define standards for metadata, schema evolution, and data partitioning.

Build and optimize data pipelines on Azure Data Services (Data Factory, Synapse, ADLS).

Develop and manage Databricks notebooks and workflows for data transformation and analytics.

Integrate cloud-native tools for monitoring, logging, and performance tuning.

Implement CI/CD pipelines for data workflows using tools like Azure DevOps, Git, and Terraform.

Automate deployment and testing of ETL jobs and data pipelines.

Actively participate in SAFe Agile ceremonies, sprint planning, and backlog grooming.

Collaborate with Product Owners, Data Architects, and Business Analysts to deliver data solutions.

Contribute to the design and implementation of data products that serve analytical and operational needs.

Ensure alignment with enterprise data strategy and governance frameworks.

Ideal Candidate

Required Skills & Qualifications

10+ years of experience in Data Engineering, with strong hands-on expertise in Informatica ETL.

Proven experience in data architecture, especially in data sourcing and data lake platforms.

Strong knowledge of Azure Data Services, Databricks, and cloud-native data engineering.

Exposure to DevOps practices and tools for data pipeline automation.

Experience working in SAFe Agile environments.

Solid understanding of data governance, metadata management, and data quality frameworks.

Excellent communication and stakeholder management skills.

Preferred Qualifications

Certifications in Azure, Informatica, or Databricks.

Experience with data mesh or data product architecture.

Familiarity with Python, SQL, and Spark.