Job type
Full-time
Location
United States - Conshohocken PA
Experience
Mid
Category
Data Engineering
Posted
2mo ago
Apply by
No deadline
We are looking for a Data Engineer to join a growing team in Conshohocken, Pennsylvania within the financial services industry. In this role, you will build and enhance modern data pipelines and warehouse structures that support reporting, analytics, and business decision-making. You will partner with technical and business teams to deliver reliable, well-governed data solutions using Python, Azure Synapse Analytics, and related cloud technologies.
Responsibilities:
• Build and support scalable data pipelines using Python, including PySpark, within Azure Synapse Analytics notebooks and pipeline workflows.
• Design, load, and maintain warehouse structures in a massively parallel processing environment, applying dimensional modeling concepts such as facts and dimensions.
• Ingest and transform data from a range of sources, including APIs, databases, and flat files, to create dependable datasets for downstream use.
• Improve the efficiency and reliability of Azure Synapse processes by tuning queries, refining workloads, and addressing performance constraints.
• Partner with data architects, analysts, and other stakeholders to translate business needs into practical data models and engineering solutions.
• Establish validation routines and data quality controls to promote completeness, consistency, and accuracy across datasets.
• Monitor scheduled jobs and pipeline activity, troubleshoot failures, and implement corrective actions to maintain service levels.
• Document data flows, transformation logic, technical configurations, and operating procedures to support maintainability and knowledge sharing.
• Apply security, privacy, and governance standards to data solutions while supporting broader data platform initiatives such as lakes, lakehouses, and cataloging practices.
• Hands-on experience in data engineering with strong capability in Python and PySpark for ETL development.
• Proficiency with Azure Synapse Analytics components, including notebooks, pipelines, linked services, and integration with Azure Key Vault.
• Solid understanding of data warehousing principles, dimensional modeling, and query optimization in SQL and SparkSQL environments.
• Experience working with version control tools such as Git, ideally within Azure DevOps.
• Strong analytical and troubleshooting skills with close attention to data accuracy and process reliability.
• Effective written and verbal communication skills with the ability to collaborate across teams and manage changing priorities.
• Familiarity with big data or analytics technologies such as Apache Spark, Hadoop, Kafka, Power BI, Tableau, or Agile delivery practices is an advantage.
Responsibilities:
• Build and support scalable data pipelines using Python, including PySpark, within Azure Synapse Analytics notebooks and pipeline workflows.
• Design, load, and maintain warehouse structures in a massively parallel processing environment, applying dimensional modeling concepts such as facts and dimensions.
• Ingest and transform data from a range of sources, including APIs, databases, and flat files, to create dependable datasets for downstream use.
• Improve the efficiency and reliability of Azure Synapse processes by tuning queries, refining workloads, and addressing performance constraints.
• Partner with data architects, analysts, and other stakeholders to translate business needs into practical data models and engineering solutions.
• Establish validation routines and data quality controls to promote completeness, consistency, and accuracy across datasets.
• Monitor scheduled jobs and pipeline activity, troubleshoot failures, and implement corrective actions to maintain service levels.
• Document data flows, transformation logic, technical configurations, and operating procedures to support maintainability and knowledge sharing.
• Apply security, privacy, and governance standards to data solutions while supporting broader data platform initiatives such as lakes, lakehouses, and cataloging practices.
Requirements
• Bachelor’s degree in Computer Science, Information Technology, or a related discipline, or equivalent relevant experience.• Hands-on experience in data engineering with strong capability in Python and PySpark for ETL development.
• Proficiency with Azure Synapse Analytics components, including notebooks, pipelines, linked services, and integration with Azure Key Vault.
• Solid understanding of data warehousing principles, dimensional modeling, and query optimization in SQL and SparkSQL environments.
• Experience working with version control tools such as Git, ideally within Azure DevOps.
• Strong analytical and troubleshooting skills with close attention to data accuracy and process reliability.
• Effective written and verbal communication skills with the ability to collaborate across teams and manage changing priorities.
• Familiarity with big data or analytics technologies such as Apache Spark, Hadoop, Kafka, Power BI, Tableau, or Agile delivery practices is an advantage.
Requirements
PythonPySparkAzure Synapse AnalyticsSQLSparkSQLGitApache SparkHadoopKafkaPower BI
Market rate — Data Engineering, United States · based on 161 similar listings, last 90 days
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