Data Engineer - Databricks

UNAVAILABLE; McLean (VA); In loco; USD 120.000 - 170.000; Tempo pieno

Descrizione del lavoro

Unknown is seeking a seasoned Data Engineer to design, build, and migrate enterprise-grade data platforms, lakes, and lakehouses using Databricks. The role emphasizes data governance, cataloging with Unity Catalog, and collaboration with teams to deliver scalable data solutions across AWS/Azure/GCP.

You will apply PySpark/Python, SQL, and cloud technologies to support governance and data processing while participating in an Agile development lifecycle.

Competenze

• Ability to obtain and maintain a U.S. government security clearance.
• Bachelor's degree in computer science, information systems, engineering, or a related technical discipline.
• 2–4 years of industry experience developing production software and solving complex technical problems.
• 2–4 years of direct experience in Data Engineering, including Databricks, Spark, Delta Lake, SQL, and data pipelines.
• Hands‑on experience implementing and working with Databricks Unity Catalog, data cataloging, governance, and permissions.
• Experience with data governance practices within Databricks data lake or lakehouse environments.
• Advanced SQL knowledge and experience with relational databases (T‑SQL, PostgreSQL, MySQL).
• Experience with large, structured and unstructured datasets; ability to modernize pipelines with Databricks.
• Experience with cloud platforms (AWS, Azure, GCP) and data lakehouse architectures.

Mansioni

• Design, develop, and support migration of data lake and lakehouse environments using Databricks for performance, reliability, and scalability.
• Implement and support Databricks Unity Catalog to enable centralized data governance and access control.
• Assess and understand existing ETL jobs, workflows, data marts, BI tools, reports, and data dependencies.
• Design, develop, and optimize scalable data pipelines and processing solutions using Databricks.
• Develop and support database, data warehouse, data mart, data lake, and lakehouse solutions in cloud environments (AWS/Azure/GCP).
• Apply hands-on expertise with Databricks, Unity Catalog, SQL, PySpark/Python, and cloud technologies to governance solutions.
• Support an Agile software development lifecycle.
• Contribute to the AI & Data Exploitation Practice growth.
• Collaborate with project teams including developers and data scientists building dashboards, reports, analytics, and ML models.

Conoscenze

Communication skills

Customer service

Problem solving

Agile experience

Formazione

Bachelor's degree in computer science/in information systems/engineering or related technical discipline

Strumenti

Databricks

Apache Spark

Delta Lake

SQL (T-SQL / PostgreSQL / MySQL)

Databricks Unity Catalog

Databricks Workflows

Airflow

AWS/Azure/GCP cloud services

Python ( PySpark )

Java

Scala

Iceberg

Informatica EDC / Collibra / Alation / Purview / DataZone

Descrizione del lavoro

Overview

We are looking for a seasoned Data Engineer to work with our team and clients to develop enterprise-grade data platforms, data lakes and lakehouses, services, and pipelines using Databricks, with a focus on data governance and cataloging using Unity Catalog. We are looking for more than just a Data Engineer; we are seeking a technologist with excellent communication and customer service skills and a passion for data and problem solving.

Responsibilities

• Design, develop, and support the migration of data lake and lakehouse environments using Databricks, with a focus on performance, reliability, and scalability.
• Implement and support Databricks Unity Catalog to enable centralized data governance, discovery, access control, and management across data lake and lakehouse environments.
• Assess and understand existing ETL jobs, workflows, data marts, BI tools, reports, and associated data dependencies.
• Design, develop, and optimize scalable data pipelines and data processing solutions using Databricks.
• Address technical inquiries concerning customization, integration, enterprise architecture, and the features and functionality of data products.
• Develop and support database, data warehouse, data mart, data lake, and lakehouse solutions in cloud environments such as AWS, Azure, or GCP.
• Apply hands‑on expertise with Databricks, Unity Catalog, SQL, PySpark/Python, and cloud technologies to support data engineering and governance solutions.
• Support an Agile software development lifecycle.
• Contribute to the continued growth of our AI & Data Exploitation Practice.

Qualifications

• Ability to obtain and maintain a U.S. government security clearance.
• Bachelor's degree in computer science, information systems, engineering, or a related technical discipline.
• 2–4 years of industry experience developing production software and solving complex technical problems.
• 2–4 years of direct experience in Data Engineering, including experience with tools and technologies such as:
  • Big data technologies: Databricks, Apache Spark, Delta Lake, or similar.
  • Relational SQL: preferably T-SQL; alternatively PostgreSQL or MySQL.
  • Data pipeline and workflow management tools: Databricks Workflows, Airflow, AWS Step Functions, or similar.
  • Cloud services: Databricks on AWS, S3, EC2, RDS, or Azure equivalents.
  • Object-oriented or scripting languages: PySpark/Python, Java, C++, Scala, or similar.
  • Data lakehouse architecture and technologies such as Delta Lake or Apache Iceberg.
• Demonstrated hands‑on experience implementing and working with Databricks Unity Catalog, including data cataloging, governance, access controls, and permissions.
• Experience applying data governance practices within Databricks data lake or lakehouse environments.
• Advanced SQL knowledge and experience working with relational databases, including query development and optimization, as well as familiarity with a variety of database technologies.
• Experience manipulating, processing, and extracting value from large, disparate datasets.
• Ability to assess existing data pipelines, understand their purpose and functionality, and efficiently reimplement or modernize them using Databricks.
• Experience working with structured and unstructured data.
• Experience architecting data systems, including transactional systems and data warehouses.
• Experience with the software development lifecycle (SDLC), CI/CD practices, and development, test, and production environments.
• Experience with additional data cataloging and governance tools such as Informatica EDC, Collibra, Alation, Microsoft Purview, or Amazon DataZone is a plus.
• Demonstrated commitment to data governance and data management best practices.
• Experience working in an Agile environment.
• Experience supporting project teams of developers and data scientists building web-based interfaces, dashboards, reports, analytics solutions, and machine learning models.