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Data Engineer
AHEAD, United States
The role
The role will support data coming from enterprise applications and services, including Salesforce, NetSuite, AHEAD applications, and approved APIs. The Data Engineer will make data available for analytics, applications, and automation through consistent engineering patterns, appropriate access controls, and dependable operational practices. The team uses AI-assisted engineering tools to accelerate delivery while maintaining security and code quality.
Working under the Director, Data Platform and alongside other data engineers, this role will partner with Analytics, source-system owners, and data consumers to implement requirements and deliver maintainable solutions through production support.
What you will do
- Build, maintain, and improve batch and incremental data ingestion pipelines to meet agreed freshness needs, including API pagination and rate limits, retries, schema changes, deletes, and replay or backfill without duplicating data.
- Use approved AI-assisted development tools for coding, testing, documentation, and troubleshooting; protect sensitive data and credentials, and validate generated output through testing, engineering judgment, and peer review.
What you need
Education and Experience
- Bachelor’s degree in computer science, information systems, engineering, mathematics, or a related field, or equivalent experience.
- 3 or more years of experience in data engineering, software engineering, analytics engineering, or a related technical role.
- Professional experience writing production-quality SQL and Python.
- Experience independently building, deploying, and supporting production data pipelines, with hands-on orchestration experience covering scheduling, dependency management, monitoring, and failed-run recovery.
- Hands-on experience with a cloud data warehouse and a transformation framework; Snowflake and dbt experience is strongly preferred.
- Understanding of relational and dimensional data modeling, keys, grain, ELT/ETL patterns, APIs, source-system integration, schema evolution, and historical-change handling.
- Experience with software engineering practices including source control, code review, automated testing, and CI/CD.
- Experience using AI-assisted development tools effectively, with critical review of generated code and tests.
- Understanding of data quality, metadata, lineage, role-based access, privacy, and secure handling of enterprise data, including secrets and service credentials.
- Ability to investigate data issues, communicate findings clearly, and work through ambiguity with teammates and stakeholders.
- Ability to collaborate effectively with engineers, analysts, source-system owners, security teams, and business stakeholders to implement and support reliable data solutions.
Physical Requirements
- Ability to safely and successfully perform the essential job functions consistent with the ADA, FMLA, and other federal, state, and local standards, including meeting qualitative and/or quantitative productivity standards.
- Ability to maintain regular, punctual attendance consistent with the ADA, FMLA, and other federal, state, and local standards.
- Primarily office and computer-based work with standard engineering and collaboration expectations for an enterprise technology role.
Nice to have
- Experience with Azure cloud storage, containerized or serverless workloads, and infrastructure as code, such as Terraform.
- Experience ingesting data from enterprise applications such as Salesforce or NetSuite using REST or GraphQL APIs.
- Familiarity with pipeline migration, observability, data catalogs, lineage tooling, or data quality platforms.
- Experience building datasets that support BI reporting or governed application access through APIs.
- Experience reconciling customer, product, order, or other business identifiers across systems, including reference data, entity matching, and historical change tracking.
- Experience supporting production pipelines or datasets with freshness monitoring, versioning, access controls, and support procedures.
- Curiosity about emerging data platform technologies and a practical approach to adopting them.
About AHEAD
The Data Engineer, Data Platform will build and operate the data capabilities that help AHEAD teams access trusted, usable, and well-managed information. This hands-on role will develop and support production ingestion pipelines, transformations, data models, and reusable data products, with an emphasis on Snowflake, dbt, SQL, and Python.
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Source: the AHEAD Lever job board. We last checked this job 2 h ago. We first saw it 2 h ago. A job on a job board does not always mean that the team interviews people now. We found this job board in a public list. We did not yet compare it with the careers page of the company.
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