Remote Senior Data Engineer

Kforce Inc; Carlsbad (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

Kforce Inc. is seeking an experienced Senior Data Engineer in California to design and own end-to-end data architecture.

You will build ingestion pipelines for partner data and API integrations, operate a curated analytics layer, and enforce HIPAA-compliant governance while partnering across backend, ML, and product teams. You will implement robust data validation, lineage, and observability, leveraging tools like PostgreSQL, dbt, and cloud primitives on AWS.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related technical field.
• 8+ years of professional data engineering experience shipping production data systems end-to-end.
• Mastery of PostgreSQL: schema design, indexing, query tuning, partitioning, JSONB, extensions, and scale.
• Experience with file-based and API-based ingestion with data validation and lineage.
• Experience with dbt and modern data modeling patterns.
• Hands-on with cloud platforms (AWS) and data primitives.
• Experience with orchestration frameworks (Dagster/Prefect/Airflow).
• Data governance in HIPAA environments and PHI/PII protection.
• Experience with ML workflows and AI coding assistants.
• Strong Python for ingestion and tooling.

Responsibilities

• Design and own end-to-end data architecture including landing zone, ingestion pipelines, and curated analytics layer.
• Build ingestion pipelines for partner data (CSV/JSON/XML/HL7/X12) and REST/SFTP with schema validation and data lineage.
• Stand up and operate curated data layer to support analytics and ML without impacting production.
• Design and operate minimal toolset (storage, orchestrator, transformations, validation library).
• Enforce data governance for HIPAA-regulated environment: encryption, RBAC, audit logs, retention, de-identification.
• Collaborate with backend, ML, product, and clinical stakeholders to define data contracts and ensure data quality.
• Maintain feature data for ML models and embeddings (e.g., pgvector).
• Instrument observability: SLAs, data freshness, schema drift, quality metrics.
• Participate in Agile ceremonies: backlog grooming, sprints, demos, retros.

Skills

PostgreSQL

Data pipelines

Python

Airflow/Dagster

dbt

Cloud (AWS)

Data governance

HIPAA knowledge

Education

BS/BA in CS/Engineering

Tools

Dagster

Prefect

Airflow

Great Expectations/Pandera/Soda

S3

pgvector

Job description

Responsibilities

• Design and own end-to-end data architecture: a landing zone with secure cloud object storage for raw partner files and API payloads, validated ingestion pipelines into our transactional Postgres, and a curated analytics layer that decouples reporting and AI workloads from production


• Build ingestion pipelines for the data we receive today, including partner data files (CSV/JSON/XML/HL7/X12 as applicable) and REST/SFTP API integrations with schema validation, quarantine of bad records, and full lineage from raw bytes to curated row


• Stand up and operate the curated layer (data warehouse/lakehouse-lite) so analytics and ML models can consume data without slowing down the transactional system


• Choose, integrate, and operate the smallest set of tools needed, including object storage, an orchestrator (Dagster, Prefect, Airflow, etc.), dbt or similar for transformations, a single validation library (Great Expectations/Pandera/Soda)


• Design and enforce data governance for a HIPAA-regulated environment: PHI/PII classification, encryption in transit and at rest, role-based access, audit logging, retention and minimum-necessary policies, and de-identification where appropriate


• Partner with backend, ML, product, and clinical stakeholders to define data contracts with our health plan and ACO partners and hold the line on data quality


• Build and maintain reliable feature data for ML models, including embeddings (e.g., pgvector) and curated feature tables for risk stratification, engagement, and outcomes work


• Instrument the data platform for observability including pipeline SLAs, data freshness, schema drift, quality metrics, and act on what the data tells you


• Participate fully in our Agile process: backlog grooming, sprint planning, demos, and retrospectives

Requirements

• BS/BA degree or higher in Computer Science, Engineering, or a related technical field


• 8+ years of professional data engineering experience, with a track record of shipping production data systems end-to-end


• Mastery of PostgreSQL: schema design, indexing, query tuning, partitioning, logical replication, JSONB, extensions (pg_partman, pg_cron, pgvector, etc.), and operating Postgres at scale


• Strong experience designing and operating data pipelines, including file-based ingestion (SFTP/object storage drops) and API-based ingestion (REST, webhooks)


• Strong experience with dbt (or equivalent SQL-based transformation framework) and modern data modeling patterns (Kimball dimensional, Data Vault, One Big Table - and an opinion about when each is right)


• Hands‑on experience with one or more cloud platforms (AWS preferred) and their data primitives: object storage (S3), managed Postgres


• Experience designing data warehouses and/or data lakes and the judgment to know which one a given problem actually needs


• Experience with at least one orchestration framework (Dagster, Prefect, or Airflow) and a clear point of view on which to use when


• Experience with data validation and data-quality frameworks (Great Expectations, Pandera, Soda, or equivalent)


• Experience with change-data-capture from Postgres (logical replication, or equivalent)


• Data governance experience in a HIPAA-regulated environment or, at minimum, demonstrated instincts for protecting PHI and PII (encryption, least privilege, audit, de-identification, BAA‑aware vendor selection); HITRUST or SOC 2 experience is a strong plus


• Experience supporting ML workloads


• Experience using AI coding assistants (e.g., GitHub Copilot, Cursor, Claude) to accelerate development


• Strong Python skills for ingestion, validation, and tooling


• Comfortable with infrastructure‑as‑code and CI/CD for data systems

The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.

We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.

Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.

This job is not eligible for bonuses, incentives or commissions.

Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.