Position Title: Data Engineer
Reports to: Engineering Lead
FLSA Classification: Exempt
Location: DMV area, hybrid – primarily remote with in-person client engagement as needed
Travel Requirements: Occasional travel within the DC-metro area for customer engagements and team on-sites
Background Check Required: Yes
Position Summary
The Data Engineer builds the pipelines and models that turn source system data into analytics customers act on, and builds the reporting layer that sits on top of them. The role spans ingestion and transformation through semantic modeling, Power BI report and dashboard development, and the performance and governance work that keeps the result trustworthy. The engineer works directly with business stakeholders to understand the question behind the request, and owns the answer from source system to dashboard. The role complements CloudAI's platform-focused data engineering work by owning the analytics and reporting layer end to end.
Key Responsibilities
Build and operate the pipelines behind the analytics.
- Build ingestion and transformation pipelines from operational systems, APIs, and files, including incremental loading, historization, and schema change handling.
- Design analytics data models, including dimensional models, conformed dimensions, slowly changing dimensions, and aggregate strategy for query performance.
- Implement data quality and reconciliation controls, with alerting that surfaces a problem before a report does.
- Orchestrate and monitor scheduled workloads with dependency management, retry behavior, and failure handling.
Build the analytics and reporting layer.
- Build Power BI semantic models, including DAX measures, relationships, row-level security, incremental refresh, and performance tuning.
- Develop reports and dashboards that answer the question the stakeholder actually asked, with attention to clarity, accessibility, and load time.
- Administer the Power BI environment, including workspaces, deployment pipelines, gateways, capacity, and usage monitoring.
- Define and document metric definitions so that a number means the same thing everywhere it appears.
Work with the people who use the data.
- Elicit reporting and analytics requirements from business stakeholders and translate them into models, measures, and visuals.
- Train and support report consumers and self-service users, and set the guardrails that keep self-service reliable.
- Document datasets, models, metric definitions, and lineage.
Contribute to CloudAI's data practice.
- Contribute to solution design, estimation, and technical approach during presales and project planning.
- Improve shared standards, reusable components, and report templates as new needs surface from engagement work.
Competencies & Skills
Technical and interpersonal competencies required to succeed in this role, spanning both hard skills (tools, technologies, methodologies) and soft skills (communication, problem-solving, stakeholder management).
Core Competencies
- Customer and Business Focus: Starts with the customer, works efficiently, and delivers lasting value through continuous improvement
- Ownership and Delivery: Takes ownership, honors commitments, moves with urgency, and delivers their best work
- Curiosity and Growth: Goes deep to understand the 'why,' stays open to new ideas, and challenges the status quo
- Candor and Collaboration: Leads with transparency, welcomes thoughtful disagreement, and chooses the path based on the merit of ideas
- Empathy and Respect: Listens to understand, respects others' perspectives, and acts as a team player
Technical Competencies
- SQL at an expert level, including query optimization, window functions, and performance tuning against large datasets.
- Power BI at depth, including semantic modeling, DAX, Power Query and M, row-level security, incremental refresh, deployment pipelines, and capacity administration.
- Python for data engineering, including pipeline development, API integration, and transformation logic.
- Data modeling for analytics, including dimensional modeling, slowly changing dimensions, and semantic layer design.
- Cloud data platforms and ELT tooling, such as Azure Data Factory, Synapse, Databricks, Snowflake, or AWS Glue.
- Data quality, governance, and lineage practice, including access control and sensitive data handling.
- Engineering practice, including Git, CI/CD, testing, and documentation, applied to both pipeline and report assets.
Delivery Competencies
- Ownership: Remains with a problem until it is resolved rather than escalating to transfer it.
- Independent judgment: Operates without supervision and determines what the work requires.
- Curiosity: Seeks to understand the customer's business, the technical solution, and the people involved rather than accepting information as given.
- Relationship building: Establishes trust with customers and delivery teams deliberately.
- Adaptability: Adjusts approach to the customer, project, and team rather than applying a fixed method.
- Clarity: Presents a number so that a non-technical stakeholder can act on it without a translator.
Education & Experience Requirements
- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent practical experience.
- Eight (8) years of professional data engineering or analytics engineering experience.
- Demonstrated experience delivering an end-to-end analytics solution from source ingestion through production reporting.
- Significant Power BI experience, including semantic model design, DAX, and performance tuning, rather than report authoring alone.
- Demonstrated experience working directly with business stakeholders to define reporting requirements and metric definitions.
- Experience supporting regulatory, compliance, or operational reporting where the numbers are scrutinized preferred.
- Experience with public sector, SLED (state, local, and education), or higher-education clients preferred, not required.
- Must physically reside in the United States and be authorized to work in the United States. U.S. citizenship or permanent residency is not required.
Certifications
- No certification required for this role.
- Microsoft certification preferred (e.g., Power BI Data Analyst Associate, Azure Data Engineer Associate, or Fabric Analytics Engineer Associate).
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