Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and sustain scalable ETL/ELT pipelines to facilitate enterprise data integration and analytics.

• Ingest, transform, and unify data from a variety of sources, including flat files, JSON, XML, Excel, REST APIs, graph databases, and other structured and unstructured data formats.

• Create and refine SQL and Python-based data processing solutions to enhance efficient data ingestion and transformation.

• Build and uphold reusable, scalable data workflows that support business intelligence, reporting, and advanced analytics.

• Load, manage, and optimize data within contemporary data platforms, such as Databricks Unity Catalog and SQL Server Managed Instances.

• Provide support for both batch and streaming data ingestion frameworks.

• Implement and uphold modern Lakehouse architecture solutions to boost scalability, performance, and accessibility.

• Monitor and enhance database and pipeline performance to ensure efficient processing and storage.

• Establish data quality controls to guarantee the accuracy, consistency, reliability, and integrity of enterprise data.

• Maintain data lineage and metadata to support governance and regulatory compliance.

• Apply enterprise data management (EDM) standards and best practices throughout the data lifecycle.

• Support data governance initiatives, including documentation, validation, and quality assurance activities.

• Collaborate with cross-functional teams, including data analysts, software developers, architects, and business stakeholders, to comprehend data requirements and deliver effective solutions.

• Support analytical environments focused on fraud detection, anomaly detection, financial oversight, and other data-driven initiatives.

• Troubleshoot and resolve issues related to data pipelines, integration, and performance while continuously enhancing existing processes.

⛳️ Requirements

• Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or a related technical field (or an equivalent combination of education and experience).

• A minimum of 3 years of professional experience in data engineering or a related discipline.

• Proven experience in designing, constructing, and maintaining scalable ETL/ELT pipelines across various data sources.

• Strong expertise in SQL and Python or comparable technologies utilized for data engineering and transformation.

• Experience in ingesting and transforming data from diverse formats, including:

• Flat files

• JSON

• XML

• Microsoft Excel

• REST APIs

• Graph databases

• Additional structured and unstructured data sources

• Experience with Databricks Unity Catalog, SQL Server Managed Instances, or similar enterprise data platforms.

• Familiarity with streaming and batch ingestion frameworks and modern Lakehouse architecture.

• Strong comprehension of data quality, data lineage, performance optimization, and enterprise data management principles.

• Knowledge of data governance, data quality, and data management practices aligned with Enterprise Data Management (EDM) standards.

• Experience supporting fraud detection, anomaly detection, financial oversight analytics, or similar analytical environments is preferred.

• Exceptional analytical, problem-solving, and communication skills with the ability to collaborate effectively across technical and business teams.

• Must be willing to undergo a U.S. Government background investigation.

🏝️ Benefits

• Competitive pay

• Comprehensive health coverage

• Flexible PTO

• Federal holidays off

• Tuition reimbursement

• Professional development support

• Wellness stipends

• A culture that values and rewards hard work, dedication, and adaptability