Responsibilities: - Design, develop, and maintain scalable data pipelines using Spark, Hive, and Airflow
- Develop and deploy data processing workflows on the Databricks platform
- Develop API services to facilitate data access and integration
- Create interactive data visualizations and reports using AWS QuickSight
- Builds required infrastructure for optimal extraction, transformation and loading of data from various data sources using AWS and SQL technologies
- Monitor and optimize the performance of data infrastructure and processes
- Develop data quality and validation jobs
- Assembles large, complex sets of data that meet non-functional and functional business requirements
- Write unit and integration tests for all data processing code
- Work with DevOps engineers on CI, CD, and IaC
- Read specs and translate them into code and design documents
- Perform code reviews and develop processes for improving code quality
- Improve data availability and timeliness by implementing more frequent refreshes, tiered data storage, and optimizations of existing datasets
- Maintain security and privacy for data at rest and while in transit
- Other duties as assigned
Minimum Qualifications: - Bachelor's degree
- 7+ years of hands-on software development experience
- 4+ years of experience building data pipelines using Python, Java, and cloud technologies, with hands-on experience leveraging Spark and Hive for large-scale data processing.
- Candidate must be able to obtain and maintain a Public Trust clearance
- Candidate must reside in the US, be authorized to work in the US, and work must be performed in the US
- Must have lived in the US 3 full years out of the last 5 years
Preferred Qualifications: - Experience building job workflows with the Databricks platform
- Strong understanding of AWS products including S3, Redshift, RDS, EMR, AWS Glue, AWS Glue DataBrew, Jupyter Notebooks, Athena, QuickSight, EMR, and Amazon SNS
- Familiar with work to build processes that support data transformation, workload management, data structures, dependency and metadata
- Experienced in data governance process to ingest (batch, stream), curate, and share data with upstream and downstream data users.
- Experienced in data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up.
- Demonstrated understanding using software and tools including relational NoSQL and SQL databases including Cassandra and Postgres; workflow management and pipeline tools such as Airflow, Luigi and Azkaban; stream-processing systems like Spark-Streaming and Storm; and object function/object-oriented scripting languages including Scala, C++, Java and Python.
- Familiar with DevOps methodologies, including CI/CD pipelines (Github Actions) and IaC (Terraform)
- Ability to obtain and maintain a Public Trust; residing in the United States
- Experience with Agile methodology, using test-driven development.
Job Location: This position requires that the job be performed in the United States. If you accept this position, you should note that ICF does monitor employee work locations and blocks access from foreign locations/foreign IP addresses, and also prohibits personal VPN connections.
Pay Range - There are multiple factors that are considered in determining final pay for a position, including, but not limited to, relevant work experience, skills, certifications and competencies that align to the specified role, geographic location, education and certifications as well as contract provisions regarding labor categories that are specific to the position.
The pay range for this position based on full-time employment is:
$89,649.00 - $152,404.00
Nationwide Remote Office (US99)
