Job Purpose :

Kellton Tech is seeking a Data Engineer who will support the design and implementation of a modern data ecosystem that will enable sophisticated business insights and on-demand operational reporting. The Data Engineering group leads the development of our Enterprise Datawarehouse/Data Lakes applications. The right individual will be passionate about data-driven information which will guide and influence key business decisions.

This role will partner with the digital product management team as well as internal clients understanding business inquiries, driving requirements, propose solutions and deliver multiple cross-functional projects and integrations between different systems. This is a unique opportunity to build and institutionalize a best-in-class data ecosystem on premise or in the public cloud. Does leading the engineering which ingests, processes, stores, and analyzes terabytes of interesting consumer data excite you? Were looking for you! In this role, youll be responsible for the development, quality and integrity of the data pipelines which deliver a diverse set of data types to other engineering teams.

Key Qualifications :

- 8+ years building and supporting production data pipelines and data models.

- Strong SQL and Python (preferred); code reviews, testing, and CI/CD.

- Snowflake + cloud data warehousing/lake platforms (Databricks/Redshift) and integration tools (Kafka, SSIS or equivalent).

- Data quality + observability: freshness/completeness checks, anomaly detection, alerting.

- Governance and security for sensitive data (PII, masking, least privilege) and safe AI use.

- Agentic delivery: decompose work, iterate plan - execute - validate, generate tests/docs, produce PR-ready increments (human-reviewed).

- Clear communicator; translate business needs into scalable solutions and concise documentation.

Duties and Responsibilities :

Responsibilities include :

- Build and run ETL/ELT pipelines and data models for the EDW and data lake.

- Deliver curated datasets/data marts for reporting, analytics, and AI.

- Implement validation, quality checks, and metadata so data is trusted and AI-ready.

- Monitor jobs, troubleshoot issues, and document root cause and fixes.

- Define SLAs and data contracts (schemas, quality thresholds); report metrics.

- Use AI-assisted and agentic SDLC to break down work, generate tests/docs/runbooks, and deliver PR-ready increments with human review.

- Apply governance and security controls (PII handling, access controls) to meet compliance.

Minimum Qualifications :

- 8+ years in production data engineering; strong SQL and Python (preferred).

- Snowflake + Databricks/Redshift; Kafka/SSIS (or equivalent); testing and CI/CD.

Preferred Qualifications :

- Consumer lending/financial services.

- Catalog/lineage, data quality, or observability tools.

- Partnering with analytics and AI/ML teams on data delivery.

- Certifications such as SnowPro Core/Advanced