Data Engineer

Tential Solutions; Conroe (TX); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Tential Solutions is seeking two Senior Data Engineers for a long-term engagement with a major banking client. Remote-friendly with a strong preference for hybrid work on-site at the client’s McLean, VA office.

You will design and optimize enterprise data pipelines, harmonize data across legacy and modern platforms, and ensure regulatory compliance. The role requires 4–5+ years in data engineering, deep PySpark/Spark/Databricks expertise, Snowflake experience, and proficiency in Python/SQL, plus

Qualifications

• 4–5+ years of data engineering experience, preferably in financial services, banking, or enterprise consulting.
• Strong PySpark, Spark, and Databricks for large-scale data transformation.
• Hands-on Snowflake data warehousing and relational data modeling experience.
• Proficient in Python and SQL; familiar with AWS or Azure cloud environments.

Responsibilities

• Architect and implement batch and streaming ETL/ELT pipelines using PySpark and Databricks for large-scale financial datasets.
• Design, build, and optimize Snowflake data warehouse models and storage layers.
• Lead data integration and migration efforts to consolidate banking and ERM/CDM data.
• Perform data validation, reconciliation, and audit trails for regulatory compliance and data integrity.

Skills

PySpark

Apache Spark

Databricks

Snowflake

ERM

SQL

Python

AWS

Azure

CI/CD

Tools

Git

Job description

Job Title: Senior Data Engineer

Location: Remote (Preference for Hybrid in McLean, VA)

Contract Type: Long-Term Contract

Openings: 2

Experience Level: 4–5+ Years

Industry Domain: Banking & Financial Services / Big 4 Consulting

Overview

We are seeking two experienced Data Engineers to join a long-term consulting engagement supporting a major banking institution through a high-profile, large-scale merger integration. You will design, build, and optimize enterprise data pipelines to reconcile, migrate, and harmonize financial data across disparate legacy and modern platforms.

Key Responsibilities

• Architect and implement robust batch and streaming ETL/ELT pipelines using PySpark and Databricks to handle large-scale financial datasets.
• Design, build, and optimize data warehouse models and storage layers in Snowflake.
• Lead data integration, transformation, and migration efforts to consolidate core banking and entity relationship data (ERM/CDM frameworks).
• Perform data validation, reconciliation, and audit trail implementations to ensure regulatory compliance and data integrity throughout the merger.
• Partner with enterprise architecture, consulting leads, and client engineering teams to automate pipelines, troubleshoot bottlenecks, and improve query performance.

Technical Qualifications

• Core Experience: 4–5+ years of dedicated data engineering experience, preferably within financial services, banking, or enterprise consulting environments.
• Data Processing & Analytics: Strong proficiency in PySpark, Apache Spark, and Databricks for large-scale data transformation.
• Data Warehousing: Hands-on expertise building schemas, optimizing queries, and managing workloads in Snowflake.
• Data Modeling: Solid understanding of ERM (Entity Relationship Management / Enterprise Reference Data), relational data modeling, and data migration strategies.
• Languages & Scripting: Advanced Python and SQL.
• Cloud & DevOps: Familiarity with AWS or Azure cloud environments, version control (Git), and CI/CD deployment workflows.

Logistics & Work Arrangement

• Location: Remote-friendly. Strong preference for candidates willing to work a hybrid schedule on-site at the client’s McLean, VA office.
• Contract Duration: Long-term engagement (multi-year program scope).