Note: The job is a remote job and is open to candidates in USA. ICF is a global advisory and technology services provider, and they are seeking a Senior Data Engineer (Databricks) to support an enterprise initiative focused on platform infrastructure and analytics modernization for a federal customer. The role involves collaborating with cross-functional teams to build scalable data solutions and ensuring that decision-makers have access to accurate and timely data.
Responsibilities
- Enable secure, scalable, and efficient data exchange between federal client and external data sharing partners using Databricks Delta Sharing
- Support the design and development of data pipelines and ETL routines in Azure Cloud environment for many source system types including RDBMS, API, and unstructured data using CDC, incremental, and batch loading techniques
- Conduct data profiling, transformation, and quality assurance on structured, semi-structured, and unstructured data
- Identify underlying issues and translate them into technical requirements
- Assist in building and optimizing data lakes, feature stores, and data warehouse structures to support analytics and machine learning
- Prepare, structure, and validate data for data science and MLOps workflows, ensuring it meets the quality and format requirements for modeling
- Help monitor and maintain the flow of data across BI dashboards, analytics environments, and machine learning pipelines
- Engage directly with clients and stakeholders to understand data needs and translate them into scalable solutions
- Collaborate with UX designers, business analysts, developers, and end users to define data and reporting requirements
- Work with external data partners to determine their data product needs and work within the Databricks platform to enable rapid prototyping and extensible use cases
- Meet with government employees at executive levels, platform stakeholders, and vendor partners
- Work within Agile teams to support iterative development, backlog grooming, and sprint-based delivery
- Provide mentorship to junior resources
Skills
- Bachelor's degree
- 5+ years in data engineering, data security practices, data platforms, and analytics
- U.S. Citizenship required due to federal contract requirements
- Ability to obtain and maintain a federal public trust clearance or equivalent client-required background investigation
- Candidate must reside in the U.S., be authorized to work in the U.S., and all work must be performed in the U.S
- Candidate must have lived in the U.S. for three (3) full years out of the last five (5) years
- 3+ years Databricks Platform Expertise – SME Level Proficiency including: Databricks, Delta Lake, and Delta Sharing
- Deep experience with distributed computing using Apache Spark
- Knowledge of Spark runtime internals and optimization
- Ability to design and deploy performant end-to-end data architectures
- 4+ years of ETL Pipeline Development building robust, scalable data pipelines
- Databricks certifications - Professional or specialty certifications
- Hands-on experience with Azure services such as Synapse, Data Factory, or Databricks
- Familiarity with data visualization tools such as Tableau, Power BI, or similar
- Machine Learning and Analytical Skills including: MLOps - Working knowledge of ML deployment and operations
- Data Science Methodologies - Statistical analysis, modeling, and interpretation
- Big Data Technologies - Experience beyond Spark with distributed systems
- Experience with deployment pipelines, including Git-based version control and CI/CD pipelines and DevOps practices using Terraform for IaC
- Emergency management domain knowledge a plus
- Advanced proficiency in data engineering and analytics using Python
- Expert-level SQL skills for data manipulation and analysis and experience with Scala, preferred but not required (Python expertise can substitute)
- Proven experience breaking down complex ideas into manageable components
- Demonstrable experience developing rapid POCs and Prototypes
- History of staying current with evolving data technologies and methodologies
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