Lead Cloud Data Engineer

Founded in 2003, IT Concepts’ core values – customer-centricity, teamwork, driven to deliver, innovation, and integrity – ensure we work together to be the best, realize objectives, and make a positive impact in our communities. We intentionally created and sustain our ITC culture that embraces change, experimentation, continuous learning, and improvement. We bring our design thinking problem solving approach that challenges assumptions, prioritizes curiosity, and invites complexity to deliver innovative, efficient, and effective solutions. As we continue to grow in the support of our government customers, we are looking for driven and innovative individuals to join our team.

IT Concepts is looking for an experienced Cloud Data Engineer to support Consumer Finance Protection Bureau. As a Lead Data Engineer, you will work with a team of consultants, engineers, and analysts to design, build and implement solutions to migrate CFPB’s data to the cloud while continuously improving data quality, security and integrity.

Responsibilities:

• Collaborate & contribute to the architecture, design, development, and maintenance of large-scale data & analytics platforms, system integrations, data pipelines, data models & API integrations.
• Create transformation path for data to migrate from on-prem pipelines and sources to AWS.
• Provide input and insights, in conjunction with Data Architects, to the client.
• Coordinate with data engineers to provide feedback and organization to team.
• Ensure that data are optimally standardized and analysis-ready.
• Prototype emerging business use cases to validate technology approaches and propose potential solutions.
• Collaborate and ensure data integrity after large scale migrations.
• Deliver high quality data assets to be used by the business to transform business processes and to enable leaders to complete data-driven analyses.
• Continuously improve data solutions to increase quality, speed of delivery and trust of data engineering team’s deliverables to enable business outcomes.
• Reduce total cost of ownership of solutions by developing shared components and implementing best practices and coding standards.
• Collaborate with team to re-platform and reengineer data pipelines from on-prem to AWS cloud.
• Work together with team members to ensure data quality and integrity during migrations.
• Lead by example and pitch in to enable successful and seamless client delivery.

Location: Preferred in DC area, but role is remote.

Requirements

• 8+ years experience related to Data Engineering.
• AWS Cloud Certificate
• Minimum of 3 years of experience in the following:
• Leading engineering teams, including task management and personnel management.
• Working in or managing data centric teams in the government or other highly regulated environments.
• Strong understanding of data lake, data lakehouse, and data warehousing architectures in a cloud-based environment.
• Proficiency in Python for data manipulation, scripting, and automation.
• In-depth knowledge of AWS services relevant to data engineering (e.g., S3, EC2, DMS,
• DataSync, SageMaker, Glue, RDS, Lambda, Elasticsearch).
• Understanding of data integration patterns and technologies.
• Proficiency designing and building flexible and scalable ETL processes and datapipelines using Python and/or PySpark and SQL.
• Proficiency in data pipeline automation and workflow management tools like Apache Airflow or AWS Step Functions.
• Knowledge of data quality management and data governance principles.
• Strong problem-solving and troubleshooting skills related to data management challenges.
• Experience managing code in GitHub or other similar tools.
• Minimum of 2 years of experience in the following:
• Hands-on experience with Databricks including data ingestion, transformation, analysis and optimization.
• Experience designing, deploying, securing, sustaining and maintaining applications and services in a cloud environment (e.g., AWS, Azure) using infrastructure as code (e.g., Terraform, CloudFormation, Boto3).
• Experience with database administration, optimization, and data extraction.
• Experience using containerization technology such as Kubernetes or Mesos.

• Minimum of 1 year of experience in the following:
• Hands-on experience migrating from an on-premise data platform(s) to a modern cloud environment (e.g. AWS, Azure, GCP).
• Linux/RHEL server & bash/shell scripting experience in on-prem or cloud environment.

Preferred Experience:

• Bachelor's Degree in related field.
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