Data Engineer (Data Lake, Data Warehouse & MDM)

About the Role

We are looking for an experienced Data Engineer to support enterprise data initiatives involving master data management, data governance, data lakes, data warehouses, and large-scale data processing platforms. The role focuses on building and enhancing data pipelines, managing complex datasets, and supporting data-driven initiatives across cloud, on-premises, and hybrid environments.

Key Responsibilities

• Create and manage a single master record for each business entity, ensuring data consistency, accuracy, and reliability.
• Implement data governance processes, including data quality management, data profiling, data remediation, and automated data lineage.
• Create and maintain multiple robust and high-performance data processing pipelines within cloud, private data centre, and hybrid data ecosystems.
• Assemble large, complex data sets from a wide variety of data sources.
• Collaborate with Data Scientists, Machine Learning Engineers, Business Analysts, and business users to derive actionable insights on data quality.
• Design and implement internal processes to automate manual workflows, optimize data delivery, and re-design infrastructure for greater scalability.
• Support and work with cross-functional teams in a dynamic environment.

Requirements
Experience

• At least 5 years of experience in a Data Engineer role.
• Experience building and operating large-scale data lakes and data warehouses.
• Experience working on projects for Master Data Management.
• Proven ability to support and work with cross-functional teams in a dynamic environment.

Data Platforms & Architecture

• Familiarity with data lake, data warehouse, and data lakehouse architectures.
• Familiarity with MDM processes such as golden record creation, survivorship, reconciliation, enrichment, and quality.
• Experience with Delta Lake and Databricks.
• Experience working with Hortonworks Data Platform or Cloudera Data Platform.

Data Governance & MDM

• Experience in data governance, including data quality management, data profiling, data remediation, and automated data lineage.
• Experience with Master Data Management (MDM) tools and platforms such as Informatica MDM, Talend Data Catalog, Semarchy xDM, IBM PIM & IKC, or Profisee.
• Experience with Metadata Management tools.
• Exposure to Data Governance processes and tools.

Big Data & Streaming Technologies

• Experience with Hadoop ecosystem and big data tools, including Spark and Kafka.
• Experience with stream-processing systems including Spark Streaming.

Database & Query Optimization

• Advanced working experience with relational SQL and NoSQL databases, including Hive, HBase, and Postgres.
• Deep understanding of SQL and the ability to optimize data queries.
• Successful experience manipulating, processing, and extracting value from large, disconnected datasets.

Programming & Development

• Experience with object-oriented and scripting languages such as Python, Java, and Scala.
• Experience applying modern development principles, including Scrum, Test-Driven Development (TDD), Continuous Integration (CI), Code Reviews

Cloud & ETL Technologies

• Experience working with cloud services using one or more cloud providers such as Azure, GCP, or AWS.
• Experience with ETL tools such as Talend Big Data, Azure Data Factory, or similar solutions.

Soft Skills

• Proven ability to support and work with cross-functional teams in a dynamic environment.