Senior Data lead / Engineer

Senior Data lead / engineer

Chicago, IL (3-day / week in Chicago office)

Duration : 9+ contract ( You may be hired after 9 months)

We are looking for a Senior Data lead / engineer with strong experience in Snowflake, Azure, Java, and Microservices to join our growing engineering team. The ideal candidate will have an investment banking background and the ability to assess existing data flows, architect and design next-generation data systems, and develop robust, scalable, and secure solutions following best engineering practices. Hybrid model with 3-day / week in Chicago office.

Key Responsibilities

Analyze and assess current data pipelines and architecture across multiple systems.

Design and implement a modern, scalable data architecture using Snowflake and Azure cloud services.

Build, test, and deploy data ingestion, transformation, and orchestration pipelines using microservices-based architectures.

Collaborate with data scientists, analysts, and application developers to enable seamless data access and insight generation.

Ensure data quality, lineage, and security across all environments.

Implement and advocate for engineering best practices - CI / CD, code reviews, unit testing, and documentation.

Optimize performance and cost for data storage and compute.

Support ongoing production systems and troubleshoot complex data issues.

Required Skills & Experience

12+ years of experience in data engineering, with at least 2+ years in investment banking or financial services.

Strong hands-on experience in Snowflake (SQL, Snowpipe, Streams, Tasks) and Azure Data Services (ADF, Data Lake, Synapse).

Proficient in Java with a solid understanding of microservices architecture and REST APIs.

Experience with data modeling, ETL frameworks, and data orchestration tools.

Understanding of data governance, compliance, and security standards in banking environments.

Familiarity with DevOps tools (Git, Jenkins, Terraform, etc.) and Agile methodologies.

Excellent problem-solving and communication skills, with the ability to work cross-functionally.

Preferred Qualifications

Exposure to real-time data streaming (Kafka, Spark Streaming).

Knowledge of financial products, trade data, and regulatory reporting.

Experience in performance tuning and cost optimization in cloud data environments.