This job offer is no longer available
About
Job Description: Data Engineer with strong DataEQ (Data Engineering Quality / Informatica Data Quality) expertise to design, build, and maintain scalable data pipelines with embedded data quality, validation, and observability. The role will focus on ensuring high data reliability, consistency, and trust across enterprise data platforms supporting analytics, reporting, and AI/ML use cases.
Role Summary: We are seeking a highly skilled Data Engineer with strong DataEQ (Data Engineering Quality Informatica Data Quality) expertise to design| build| and maintain scalable data pipelines with embedded data quality| validation| and observability. The role will focus on ensuring high data reliability| consistency| and trust across enterprise data platforms supporting analytics| reporting| and AIML use cases.
Key Responsibilities: Data Engineering Pipeline DevelopmentDesign| develop| and maintain robust| scalable data pipelines using batch and streaming frameworks. Build and optimize ETLELT workflows across structured and semi-structured data sources. Implement data ingestion from multiple systems (databases| APIs| files| cloud storage). Data Quality DataEQ Implementation: Implement DataEQ frameworks forData profiling| validation| completeness| accuracy| and consistency checksRule-based and threshold-based quality controls Anomaly detection and trend monitoring Integrate Informatica Data Quality (IDQ DataEQ) or equivalent data quality tools into data pipelines. Define and maintain data quality rules| scorecards| and KPIs aligned to business requirements. Proactively identify| triage| and resolve data quality issues across upstream and downstream systems. Data Governance: Observability Collaborate with data governance teams to enforce data standards| metadata management| and lineage. Enable data observability through monitoring| alerting| and logging mechanisms. Support auditability| compliance| and traceability of enterprise data assets. Platform Cloud: Enablement Work with cloud-based data platforms (AWS Azure GCP) and modern data stacks. Optimize data storage| performance| and cost across data lakes| warehouses| and lakehouses. Partner with DevOps teams to implement CICD for data pipelines and quality checks. Stakeholder Collaboration: Work closely with business analysts| data scientists| and product teams to translate requirements into data solutions. Provide data quality insights and recommendations to improve downstream analytics and decision-making. Support incident analysis and root-cause investigation for data-related issues.
Required Skills: Qualifications: Core Technical Skills Strong experience in Data Engineering (6 years preferred). Hands-on expertise with DataEQ Informatica Data Quality (IDQ) or similar data quality platforms. Proficiency in SQL and at least one programming language (Python preferred). Experience with ETLELT tools and orchestration frameworks (Airflow| Informatica| dbt| etc.). Strong understanding of data quality dimensions (accuracy| completeness| timeliness| consistency). Data Platforms Tools: Experience with data lakes and data warehouses (Snowflake| BigQuery| Redshift| Synapse| etc.). Familiarity with cloud services (AWS Azure GCP). Knowledge of metadata| lineage| and data governance concepts. Soft Skills Strong analytical and problem-solving abilities.
Diverse Lynx LLC is an Equal Employment Opportunity employer. All qualified applicants will receive due consideration for employment without any discrimination. All applicants will be evaluated solely on the basis of their ability, competence and their proven capability to perform the functions outlined in the corresponding role. We promote and support a diverse workforce across all levels in the company.
Languages
- English
Notice for Users
This job was posted by one of our partners. You can view the original job source here.