Role Overview:
We are seeking a hands-on Data Engineer with 5+ years of experience to support data engineering and master data management initiatives. The ideal candidate brings practical Databricks expertise, strong experience working with structured and semi-structured data (particularly JSON), and hands-on exposure to Reltio MDM. This is an initial three-month contract with a strong possibility of extension based on project needs and performance.
About Teqfocus:
Teqfocus is a Data and AI company that helps enterprises build and scale the Agentic Enterprise - connecting the data foundation, the intelligence layer, and the applications teams run their businesses on into a single, coherent architecture.
As a Salesforce Summit Partner, we work in Healthcare, Life Sciences, Financial Services, Insurance, and Hi-Tech - industries where getting AI right matters and the tolerance for failure is low. Our delivery model is senior-heavy by design. The same team that scopes an engagement ships it to production. There are no junior shadow teams, no sub-contractors brought in when the problem gets hard, and no hand-off to a separate managed services vendor when the project closes.
We run an internal innovation practice that builds the reusable patterns, pre-tested architectures, and industry-specific frameworks that give every Teqfocus client a head start - and give every Teqfocus practitioner work that compounds over time.
We are a diverse, immigrant-entrepreneurial company. We were built on the conviction that the best outcomes come from people who take genuine ownership of what they build - and are trusted to do so.
www.teqfocus.com
Key Responsibilities:
- Design, develop and maintain reliable data ingestion, transformation and processing pipelines using Databricks and SQL/Python-based tooling.
- Process, parse, transform and validate structured and semi-structured datasets, including nested JSON payloads from source systems and APIs.
- Work with Reltio MDM data models, records and integrations to support master data quality, synchronization and downstream consumption.
- Implement data mapping, cleansing, deduplication, reconciliation and validation checks to improve accuracy and consistency.
- Collaborate with analysts, architects and application teams to translate source-to-target requirements into robust data solutions.
- Troubleshoot pipeline failures, data discrepancies and performance bottlenecks; document mappings, assumptions and operational handoffs.
Required Skills & Qualifications:
- 5+ years of professional experience in data engineering or a closely related data integration role.
- Hands-on experience with Databricks for data processing, transformations and pipeline development.
- Strong proficiency in SQL and working knowledge of Python and/or PySpark.
- Practical experience handling JSON data, including nested structures, schema mapping, parsing and transformation.
- Working experience with Reltio MDM, including master data concepts such as entities, relationships, match/merge and data quality.
- Ability to integrate, validate and troubleshoot data across multiple source and target systems.
- Strong communication skills and ability to contribute effectively within a hybrid delivery team.
Good to Have:
- Experience with Delta Lake, Spark performance tuning and Databricks workflows/jobs.
- Experience integrating REST APIs or cloud-based data platforms.
- Familiarity with data governance, metadata management and MDM survivorship rules.
