Data Engineer

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

📋 Description

• Design and manage dependable data integrations and data platform functionalities.

• Develop new data ingestion feeds and interfaces.

• Oversee and resolve issues with current interfaces.

• Enhance ingestion processes, validation, and monitoring systems.

• Collaborate with stakeholders to provide analytics, warehousing, and reporting solutions.

• Automate environments and standardize deployment practices.

• Increase observability and reliability for data services.

• Apply changes and improvements to internal flat file and message processing services.

• Engage with clients and their technical teams.

• Assist in the design and development of analytics initiatives.

• Identify enhancement opportunities through data analytics.

• Maintain documentation related to datasets and analyses.

• Utilize generative AI in engineering tasks.

⛳️ Requirements

• 3 to 5 years of experience.

• Bachelor's Degree or equivalent experience in Computer Science.

• Over 2 years of coding experience with Microsoft SQL.

• More than 1 year of experience with big data technologies such as Databricks, Apache Spark, Python, and Microsoft Azure (Data Factory, Dataflows, Azure Functions, Azure Service Bus).

• Knowledge of engineering fundamentals: testing automation, code reviews, telemetry, iterative delivery, and DevOps.

• Experience with polyglot storage architectures, including relational, columnar, key-value, graph, or similar technologies.

• Some familiarity with BI tools, preferably Power BI.

• Understanding of operational excellence practices like incident response and runbooks.

• Knowledge of security fundamentals for cloud platforms (identity and access management, secrets management, encryption, and audit logging).

• Experience with packaging and running services using containers and orchestration (e.g., Docker, Kubernetes) and/or serverless architectures.

• Proficiency in CI/CD, version control, and release automation for data pipelines and platform components (e.g., Azure DevOps/GitHub Actions).

🏝️ Benefits

• Healthcare coverage.

• Paid time off.

• Retirement plan options.

• Opportunities for professional development.

• Incentive programs on a quarterly and annual basis.