The Data Engineer will be responsible for:

Data Strategy and Governance

• Partner with data management and business stakeholders to design and implement scalable data solutions that align with enterprise data strategy and governance frameworks.
• Contribute to defining and enforcing data standards, ensuring consistency, traceability, and adherence to architectural principles across ingestion, transformation, and consumption layers.
• Collaborate with data stewards and governance teams to promote data quality, lineage visibility, and stewardship processes within Azure and Snowflake ecosystems.
• Support efforts to transition ad hoc, manual data processes into governed, automated, and well-documented pipelines that improve transparency, auditability, and reusability
• Ensure compliance with security, privacy, and regulatory requirements across all aspects of data storage, movement, and access.

Data Engineering and Operations

• Create and manage data ingestion pipelines, setting up and maintaining data feeds and supporting both batch and near real-time integrations across internal and external systems to integrate them into the firm's environment securely and efficiently, in collaboration with the firm’s software engineers and internal applications.
• Apply strong SQL engineering skills to optimize performance across Snowflake, Azure, and PostgreSQL, leveraging stored procedures, views, ingest and transformation tools and performance tuning techniques.
• Implement transformation logic and data workflows, adhering to version control and continuous integration/continuous delivery (CI/CD) pipelines.
• Establish observability and monitoring frameworks to ensure data reliability, pipeline health, and SLA compliance.
• Collaborate with data architects to align solutions with enterprise data models, ensuring scalability, maintainability, and cost efficiency for both OLTP and OLAP paradigms.
• Contribute to tool evaluation and deployment, architecture reviews, and process automation to continually enhance data platform performance and maturity.

Reporting and Analytics

• Partner with analytics and BI teams to ensure availability and reliability of curated, high-quality data sets that power reporting and machine learning initiatives.
• Build and optimize semantic layers and curated datasets for Power BI and other visualization tools, supporting self-service analytics and governed data access.
• Contribute to data cataloging, lineage documentation, and metadata management initiatives to enhance discoverability and reusability across the enterprise.
• Collaborate closely with data consumers to understand analytical needs, ensuring that data models and transformations align with business requirements and performance expectations.

Innovation and Continuous Improvement

• Evaluate and introduce new technologies, frameworks, and methodologies that improve data processing efficiency, quality, and scalability.
• Lead or contribute to POCs and platform modernization efforts, helping evolve toward cloud-native and metadata-driven architectures.
• Continuously improve CI/CD processes, data testing, and documentation standards to promote reliability and repeatability.
• Champion best practices in data engineering, including modular design, reusable components, and performance optimization.
• Stay current with emerging trends in cloud data architecture, data mesh, and automation tools to ensure the organization remains innovative and competitive.

SKILLS DESIRED

Qualifications & Experience

• Education: Bachelor’s degree (BA/BS) in Data Engineering, Computer Science, Information Systems, or a related field. Master’s degree a plus.
• 4-7 years of experience in roles related to data engineering or related roles.
• Strong proficiency in SQL with Azure, PostgreSQL and Snowflake
• Strong proficiency in Python, Java, and other programming languages.
• Hands-on experience with Azure Data Factory, Apache Airflow, Mulesoft, and Apache Airflow for orchestration and scheduling
• Strong knowledge of data integration and ETL/ELT processes, and transformation tools, such as DBT or Coalesce.
• Experience implementing CI/CD pipelines for data infrastructure and deployments (e.g., using Azure DevOps or GitHub Actions).
• Demonstrated knowledge of data modeling, metadata management, and data lineage tools.
• Familiarity with data governance, quality frameworks, and compliance standards.
• Experience in financial services or legal industries is preferred but not required.

Pay: $125,000.00 - $140,000.00 per year

Work Location: Remote