Resumo da vaga

Data Engineer

Requisitos e responsabilidades

Conteúdo da vaga extraído em seções para revisão mais rápida.

Our values:

  • People-First: Emphasizing the importance of people in all aspects of work.
  • Collaboration and Transparency: Valuing teamwork and open communication.
  • Growth Mindset: Encouraging innovation and continuous improvement.
  • Creating Lasting Impact: Focusing on meaningful outcomes and positive change.

Responsibilities:

  • Lead the design and implementation of complex data ingestion pipelines using PySpark, Databricks Intelligence Platform, and AWS services (S3, IAM roles and policies), including Kafka/streaming architectures, schema evolution, and Delta Share, ensuring alignment with enterprise architecture standards.
  • Serve as a subject matter expert (SME) for data engineering, providing technical guidance and mentorship to engineers across the team and representing data engineering in cross-functional discussions.
  • Take ownership of platform reliability and performance, proactively identifying optimization opportunities across data ingestion, transformation, and storage layers. Troubleshoot complex pipeline failures across multi-system dependencies.
  • Lead cross-functional technical initiatives, collaborating with data scientists, analysts, DevOps engineers, client teams (upstream data providers and downstream consumers), and stakeholders to deliver integrated solutions that meet program objectives.
  • Contribute to the data platform technical vision and architecture, making strategic decisions on tooling, frameworks, and design patterns that shape the program's long-term data engineering direction.
  • Define and enforce engineering standards, including code quality, testing practices, CI/CD processes, and infrastructure as code patterns using Terraform.
  • Evaluation of new technologies and approaches, presenting proof of concepts and technical roadmaps to leadership.
  • Author and maintain architectural documentation, technical decision records, and platform runbooks that enable team autonomy and operational excellence.
  • Other relevant duties as assigned and qualified/trained to perform

Qualifications:

  • Bachelor’s degree.
  • Minimum of 5 years of experience in Data Engineering.
  • Demonstrated experience serving as a technical SME and leading cross-functional engineering initiatives.
  • Proficiency in Python for data engineering tasks at scale.
  • Deep expertise with Databricks Intelligence Platform (Notebooks, Lakeflow Jobs, Unity Catalog, Delta Share) and the ability to define platform standards and best practices for the team.
  • Experience with AWS services such as S3 and IAM roles and policies.
  • Strong knowledge of data pipeline design and implementation, including data transformation techniques, data modeling, data storage optimization, and data security best practices.
  • Proficiency in using version control systems like Git for managing code repositories and collaborating with team members on Agile projects.
  • Familiarity with Terraform or other infrastructure as code tools for automating infrastructure deployment and configuration management.
  • Experience working on Linux environments for data engineering projects, including accessing containers remotely, installing packages, managing files, services, and processes.
  • Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
  • Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
  • Strong problem-solving skills, ability to work independently and as part of a team, and excellent verbal and written communication skills.
  • Comfortable working in a highly collaborative environment with strong attention to detail and a commitment to delivering high-quality software.
  • Ability to obtain and maintain a Public Trust security clearance.

Nice to Have Skills and Experience:

  • Bachelor’s degree in a technology field.
  • Familiarity with cloud computing concepts, particularly as they apply to data engineering, is a plus.
  • Experience working with other data frameworks such as Apache Hive, Apache Hadoop, or Apache Spark is a plus.
  • Federal consulting experience
  • Databricks certifications (Associate Data Engineer or Professional Data Engineer).
  • Experience with business intelligence tools (e.g., QuickSight, Power BI) for building data observability or usage reporting.

How We Support Our Team:

  • Flex hours
  • 401K with matching incentive
  • Parental Leave
  • Medical/dental/vision benefits
  • Flex Spending Account
  • Company provided short-term disability and life insurance
  • Commuter benefits
  • Paid Time Off (PTO)
  • 11 Paid holidays
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FocoData EngineeringÁrea da vaga
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StackAWS, CI/CD, PythonSkills principais
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