Data Engineer II

Spectraforce
Tampa, FL, United States
2 months ago

Role details

Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Microsoft Azure Encodings Information Engineering Data Governance Data Infrastructure Extract Transform Load (ETL) Data Migration Relational Databases Document-Oriented Databases Python (Programming Language) PostgreSQL Microsoft SQL Server
+13 more
MySQL Performance Tuning Software Architecture Reference Data Power BI Software Tools SQL Databases Apache Spark Microsoft Fabric Data Lakes Data Management Code Restructuring Data Pipelines

Job description

Client Real Estate is seeking an Data Engineer to play a key role in modernizing the firm’s data platform and advancing its data and analytics capabilities. This is a transformational role directly aligned with client Real Estate’s commitment to leveraging data, analytics, and technology to proactively address business challenges and unlock new opportunities. 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., * 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.

Requirements

  • 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 modernizing 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.

About the company

As one of the largest real estate managers in the world with $179.2 billion in gross assets under management and administration1, PGIM Real Estate strives to deliver exceptional outcomes for investors and borrowers through a range of real estate equity and debt solutions across the risk-return spectrum. PGIM Real Estate is a business of PGIM, the $1.3 trillion global asset management business of client. Client’s Real Estate’s rigorous risk management, seamless execution, and extensive industry insights are backed by a 50-year legacy of investing in commercial real estate, a 140-year history of real estate financing 2, and the deep local expertise of professionals in 31 cities globally. Through its investment, financing, asset management, and talent management approach, Client Real Estate engages in practices that ignite positive environmental and social impact, while pursuing activities that strengthen communities around the world.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on leoforce.us

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:09 min

Balancing data science skillings alongside systems engineering rigor

Nico Schmidt · LIVE

3:17 min

Optimizing character encoding with Kim variable byte encoding

Douglas Crockford Douglas Crockford · WWC 2024

1:46 min

Traditional data architecture before Microsoft Fabric

Dr. Alexander Wachtel Dr. Alexander Wachtel +1 · WWC 2025

2:18 min

Scaling MySQL databases for massive user growth

Johannes Nicolai Johannes Nicolai +1 · LIVE

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

4:12 min

Distilling cross-encoder models into smaller efficient sentence embedding models

Marek Suppa · LIVE

Videos

See all

Related articles

See all