Data Engineer

Talentify; Newark (NJ); On-site; USD 100,000 - 150,000; Full time

Job summary

Talentify in Newark, NJ is seeking a Data Engineer to enhance ETL pipelines, build SQL-based transformations, and lead migration to Microsoft Fabric for trusted analytics-ready data.

You will partner with the Data Management team to enforce data quality, develop scalable data models, and support governance and reporting through Power BI while delivering robust data solutions in a hybrid environment.

Qualifications

• Bachelor's degree required.
• 3+ years in a data engineering or analytics role.
• Strong SQL with complex transformations, tuning, and modeling.
• Experience with ETL pipelines in on-prem or hybrid environments; PostgreSQL preferred.
• Experience migrating data platforms to Azure and/or Microsoft Fabric.
• Understanding of data lake/warehouse architectures.
• Knowledge of SQL, Python, Spark or similar tech.
• Experience with relational DBs: PostgreSQL, SQL Server, MySQL.

Responsibilities

• Maintain and enhance ETL pipelines for on-prem data lake (PostgreSQL).
• Refactor and migrate ingestion and orchestration to Microsoft Fabric.
• Design and maintain SQL-based transformations, views, and datasets.
• Build data models to support analytics and Power BI reporting.
• Apply data quality rules and automated checks in pipelines.
• Collaborate with analytics and reporting teams for consumption needs.
• Document pipelines, logic, and architectural decisions.

Skills

SQL

Python

Spark

Data modeling

ETL pipelines

Agile collaboration

Communication

Education

Bachelor's degree

Tools

PostgreSQL

SQL Server

MySQL

Azure

Microsoft Fabric

Power BI

Job description

Position Summary

The Data Engineer will be responsible for supporting and enhancing existing ETL processes for the on-prem data lake (PostgreSQL) while leading the evolution and migration of these processes to Microsoft Fabric. This role will focus heavily on developing and maintaining SQL-based transformation logic to ensure high quality, trusted, and analytics ready data. Working closely with the Data Management team, the Data Engineer will help identify, remediate, and prevent data quality issues by encoding validation rules and controls directly into data pipelines. The role will also contribute to the evaluation and implementation of tools and frameworks supporting data governance, architecture, and data quality as the platform continues to evolve.

Duties & Responsibilities

• Support and enhance existing ETL pipelines for an on-premises data lake environment, primarily backed by PostgreSQL.
• Refactor and migrate data ingestion, transformation, and orchestration processes to Microsoft Fabric using modern cloud-native patterns.
• Design, develop, and maintain complex SQL-based transformation logic, including views, functions, and analytical datasets.
• Build and optimize data models to support analytics and reporting use cases, including Power BI semantic models.
• Perform aggregations and transformations across multiple data models (e.g., normalized, dimensional, lakehouse) to enable reliable insights.
• Partner closely with data analytics and reporting teams to understand consumption needs and ensure data is structured for performance, usability, and scalability.
• Implement and enforce data quality rules, validation checks, and automated error detection within ETL and transformation workflows.
• Support master and reference data processes, including defining data quality criteria, uniqueness rules, and remediation approaches.
• Collaborate with domain owners and data stewards to analyze root causes of data quality issues and drive corrective actions.
• Monitor cross-domain data provisioning to ensure data is sourced from approved and governed systems.
• Contribute to the evaluation and implementation of data governance, architecture, and quality tools in partnership with Global Technology teams.
• Document data pipelines, transformation logic, and architectural decisions to support maintainability and knowledge sharing.

Preferred Qualifications

The successful candidate brings a structured, detail-oriented approach and a hands-on mindset toward advancing the organization's data platform modernization.

• Bachelor's degree required.
• Minimum of 3+ years of experience in a data engineering or analytics engineering role.
• Strong hands-on experience with SQL, including complex transformations, performance tuning, and data modeling.
• Experience supporting ETL pipelines in an on-prem or hybrid data lake environment; exposure to PostgreSQL strongly preferred.
• Experience migrating or modernising data platforms to Azure and/or Microsoft Fabric (Lakehouse, Pipelines, or related services).
• Solid understanding of modern data lake and warehousing architectures.
• Working knowledge of data engineering tools and languages such as SQL, Python, Spark, or similar technologies.
• Experience with at least one relational database platform (PostgreSQL, SQL Server, MySQL).
• Familiarity with data governance, data quality, or MDM concepts and tooling.
• Experience working in an agile, collaborative, cross-functional environment.
• Strong written and verbal communication skills; able to translate business requirements into technical solutions.
• Highly analytical detail-oriented problem solver with a proactive, self-starter mentality.
• Comfortable working in evolving environments and translating conceptual requirements into pragmatic, scalable solutions.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender, identity, national origin, disability, or protected veteran status.