Data Engineer

Overview

Senior Product Software Data Engineer focused on designing, developing, and troubleshooting enterprise data solutions. You will build and optimize real-time and batch data pipelines and partner with stakeholders to operationalize ML models.

What you'll do

• Collaborate with cross-functional teams to translate business requirements into scalable data solutions.
• Design and develop optimized enterprise data pipelines for real-time and batch processing.
• Analyze business processes, identify gaps, and recommend data-driven improvements.
• Build real-time data solutions using Scala, Apache Spark, and Azure Databricks.
• Partner with data scientists and stakeholders to operationalize machine learning models.
• Ensure data quality and integrity using validation frameworks and monitoring mechanisms.
• Mentor junior engineers and contribute to peer reviews and technical documentation.

What you'll need

• 3+ years overall experience in data engineering or related fields.
• 2+ years building data pipelines for structured and unstructured data.
• 1+ years experience with big data technologies including PySpark, Hadoop, Kafka, EventHub, and Stream Analytics.
• 2+ years experience with Azure Data Factory, Azure Data Lake, Azure SQL DB, and Azure Synapse Analytics.
• 2+ years experience with T-SQL, stored procedures, and performance tuning.
• Experience with relational and dimensional data modeling using SQL Server and data warehousing concepts.

Nice to have

• Good to have 2+ years experience with Azure ML, Python, and Scala.
• Good to have 2+ years experience with Power BI and Azure Analysis Services.
• Azure Data Engineer Certification or equivalent is a strong advantage.
• Experience with Agile/Scrum methodologies and DevOps practices.
• Familiarity with CI/CD pipelines and version control systems (e.g., Git).

Details

• Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.