Analytics Data Engineer

Corner Alliance

Analytics Data Engineer providing support for data driven decisions to improve federal grant outcomes. Collaborating with teams to design and implement data pipelines for program analysis.

Posted 7/28/2026full-time🇺🇸 United StatesMid-LevelSenior💰 $100,000 - $120,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing scalable data pipelines using Python, PySpark, and SQL, while leveraging cloud platforms like Azure, AWS, or GCP. Proficient in data modeling, automation, and advanced analytics to enhance decision-making and operational efficiency.

Highest-signal resume keywords

Data Pipeline DevelopmentPython ProgrammingCloud Platform ExperienceData Modeling Best PracticesAutomation Scripting

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DesignETL ProcessesPythonPySparkSQLData WarehousingData Lake ManagementAutomation ScriptingAdvanced AnalyticsData Analysis

Soft Skills

CollaborationCommunicationProblem-Solving

Tools & Technologies

DatabricksAzureAWSGCP

Industry Keywords

Data EngineeringData Development Life CycleData GovernancePublic Trust ClearanceBusiness Analytics

Tech Stack

Tools & technologies

AWSAzureCloudCyber SecurityETLGoogle Cloud PlatformPySparkPythonSQL

About the role

Key responsibilities & impact

Provide support in making data driven decisions that improve grant program outcomes
Work with data solutions architect to establish a data platform strategy
Provide direct technical expertise in the design, development, implementation and testing of different data pipelines
Collaborate with team members to design, document and implement a data development life cycle to enforce consistency and uniformity of process using Databricks and cloud tooling
Responsible for analyzing and understanding data sources, participating in requirement gathering, and providing insights and guidance on data technology and data modeling best practices
Leverage knowledge of data models, data relationships, mapping lineage and business rules to ensure that solutions meet operational and business needs
Implement and maintain end-to-end data pipelines and data systems in Databricks integrating CI/CD processes, continuously improving the quality of deliverables
Establish an authoritative Lakehouse within the Analytics Platform to organize and structure data required for post-award reporting and monitoring
Refresh and refine existing dashboarding and data analysis products (e.g., program financials, risk management, customer engagement)
Leverage advanced analytics (such as LLMs and Artificial Intelligence) to analyze unstructured program data to reduce the burden of manual review of post-award submissions, enhance ability to identify instances of fraud, waste, and abuse, and inform decision-making for effective management of project implementation
Collaborate with business stakeholders and team members to identify automation opportunities

Requirements

What you’ll need

Bachelor's degree or higher in a related field, such as computer science, engineering, business analytics, information systems management, cybersecurity, engineering
6+ year’s experience in a data engineer role or related role
Experience with the design and build of scalable data pipelines to extract, transform, and load (ETL) data from various sources
Experience utilizing programming languages like Python, PySpark, and SQL to manipulate and clean data
Experience developing and implementing automation scripts to streamline data processing tasks
Experience with the deployment, configuration, and maintenance of data storage systems like data warehouses and lakes
Experience working with cloud platforms such as Azure, AWS, or GCP
US citizenship and the ability to pass public trust clearance or suitability

Benefits

Comp & perks

401k matching (4%)
PTO (3 weeks to start, 4 weeks (2-5 years) and 5 weeks (5 years+))
Health, dental, vision insurance
Short- and long-term disability
FSA accounts
4 weeks of paid parental leave
11 paid holidays (including your birthday off)
Fitness & cell phone reimbursements
Monthly all hands update meetings
Annual in-person all hands team building day and evening out
Regular check-ins for professional growth goals
Semi-monthly one-on-one performance manager meetings
A social team that coordinates monthly events
Use of technology like Slack to keep us connected and collaborative