Data Engineer (Remote)

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