Data Architect

Data Engineering Lead/Architect

Location: St. Louis Area, MO

Employment type: Contract-to-Hire

Banking

Experience:

Highly preferred

Ideal Candidate: Experienced in a banking data modernization effort previously and can help lead/mentor the data engineering team. This individual needs to have a good solutioning/creative mindset and be willing to speak up.

• Provide technical leadership in modernizing legacy data ingestion, ETL/ELT, and databases to cloud technologies (AWS/Azure).
• Demonstrate a self-driven, ownership mindset to navigate ambiguity, resolve constraints, and mitigate risks with minimal supervision.
• Implement data access, classification, and security patterns that comply with regulatory standards (PII, locational data, contractual obligations, etc.).
• Build strong relationships with technical teams through effective communication, presentation, and collaboration skills.
• Collaborate with stakeholders, business analysts, and SMEs to translate business requirements into scalable solutions.
• Integrate data from multiple sources into cloud-based architectures, collaborating with cross-functional teams.
• Work closely with data scientists, analysts, and stakeholders to meet data requirements with high-quality solutions.
• Function within a matrixed team environment, sharing responsibilities across various teams.
• Perform data profiling and analysis on both structured and unstructured data.
• Design and map ETL/ELT pipelines for new or modified data streams, ensuring integration into on-prem or cloud-based data storage.
• Automate, validate and maintain ETL/ELT processes using technologies such as Databricks, ADF, SSIS, Spark, Python, and Scala.
• Proactively identify design, scope, or development issues and provide recommendations for improvement.
• Conduct unit, system, and integration testing for ETL/ELT solutions, ensuring defects are resolved.
• Create detailed documentation for data processes, architectures, and workflows.
• Monitor and optimize the performance of data pipelines and databases.

• Experience in designing and implementing data warehouse and analytics solutions (on-premise and cloud).
• Expertise in data warehousing concepts (ETL/ELT, data quality management, privacy/security, MDM) with hands-on experience using ADF, Data Factory, SSIS, and related tools.
• Experience with cloud data and cloud-native data lakes/warehouses. Microsoft Azure services (Fabric Lakehouse, ADF, Data Factory, Synapse, etc.).
• Experience in Python, Scala, or Java for use with distributed processing and analytics, such as Spark.
• Familiarity with CI/CD practices and tools such as Azure Dev Ops, Git, or Jenkins.

• Proven ability to mentor team members and guide best practices for data engineering.
• Strong problem-solving skills with high attention to detail.
• Excellent communication skills for effective collaboration with diverse teams.

• Experience with Snowflake, Databricks, AWS
• Experience with containerization, microservices, streaming, and event-sourcing architecture patterns.
• Knowledge of Kafka, Eventstream, architectures.
• Experience with Microsoft Purview
• Previous experience in the financial or banking sector.
• Familiarity with machine learning concepts and frameworks.
• Experience with reporting tools such as Power BI or Tableau.

• Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience).