Senior Data Engineer – Dallas, TX | Onsite | 12-Month C2C

Job Overview

 Senior Data Engineer Dallas  We are seeking an experienced Senior Data Engineer Dallas to join an enterprise data engineering initiative in Dallas, Texas. The ideal candidate will have 12+ years of experience with strong hands-on expertise in Databricks, PySpark, Python, Snowflake, data warehousing, and ETL/ELT development.

The selected candidate will be responsible for designing, developing, optimizing, and supporting scalable data pipelines and enterprise data platforms. Strong experience working with large-scale data environments and modern cloud data technologies is highly desirable.

Position Details

Job Title: Senior Data Engineer
Location: Dallas, TX
Work Arrangement: Onsite
Duration: 12 Months
Employment Type: C2C Contract
Experience: 12+ Years
Work Authorization: Any Visa Accepted
Specialization: Databricks / PySpark / Python / Snowflake / Data Engineering

Key Responsibilities

• Design, develop, and maintain scalable data pipelines for enterprise data platforms.
• Build efficient ETL/ELT workflows using Databricks, PySpark, and Python.
• Develop and optimize data processing solutions using Apache Spark.
• Work with Snowflake to develop and maintain cloud-based data warehouse solutions.
• Design data models and structures to support analytics, reporting, and business intelligence requirements.
• Develop data ingestion and transformation processes from multiple source systems.
• Implement reliable and reusable data engineering frameworks.
• Perform data cleansing, transformation, validation, and quality checks.
• Optimize Spark jobs and data pipelines for performance and scalability.
• Troubleshoot pipeline failures, data quality issues, and production problems.
• Monitor data workflows and ensure reliable data delivery.
• Collaborate with Data Architects, Data Scientists, Analysts, Developers, QA teams, and business stakeholders.
• Participate in technical design and architecture discussions.
• Develop technical documentation for pipelines, data models, ETL processes, and integrations.
• Support production deployments and resolve data-related incidents.
• Follow enterprise standards for data security, governance, quality, and development.

Databricks & PySpark

Strong hands-on experience with Databricks and PySpark is required.

The candidate should have experience:

• Developing Databricks notebooks and jobs.
• Building scalable Spark-based data pipelines.
• Processing large datasets using PySpark.
• Optimizing Spark transformations and jobs.
• Troubleshooting distributed data processing workloads.
• Implementing efficient data ingestion and transformation solutions.
• Working with modern lakehouse/data platform architectures.

Python

• Strong hands-on Python development experience.
• Experience using Python for data engineering, automation, and data processing.
• Ability to develop reusable and maintainable Python applications and scripts.
• Experience integrating Python with Databricks and Spark-based pipelines.

Snowflake & Data Warehousing

• Strong experience with Snowflake.
• Experience developing and maintaining enterprise data warehouses.
• Strong SQL and data transformation experience.
• Understanding of data warehouse architecture and dimensional modeling.
• Experience loading and transforming large datasets into Snowflake.
• Ability to optimize queries and data warehouse workloads.
• Experience supporting reporting and analytics environments.

ETL / ELT

• Strong understanding of ETL and ELT processes.
• Design and develop data pipelines that integrate multiple data sources.
• Implement data transformation, cleansing, and validation processes.
• Ensure data pipelines are reliable, scalable, and maintainable.
• Troubleshoot ETL/ELT failures and data quality issues.
• Support batch and, where required, near-real-time data processing.

Data Engineering

The successful candidate should have strong knowledge of modern data engineering concepts, including:

• Data pipelines
• Data integration
• Data warehousing
• Data modeling
• ETL/ELT
• Data quality
• Distributed processing
• Cloud data platforms
• Performance optimization
• Production support

Required Qualifications

• 12+ years of professional experience in data engineering or related technology roles.
• Strong hands-on experience with Databricks.
• Extensive PySpark experience.
• Strong Python development skills.
• Strong Snowflake experience.
• Enterprise data warehouse experience.
• Strong ETL/ELT development experience.
• Strong SQL skills.
• Experience designing and supporting large-scale data pipelines.
• Strong analytical and troubleshooting abilities.
• Excellent communication and collaboration skills.
• Ability to work onsite in Dallas, TX.
• Any visa status accepted, subject to engagement requirements.

Ideal Candidate

The ideal candidate is a senior-level data engineering professional who can work across Databricks, PySpark, Python, Snowflake, ETL/ELT, and enterprise data warehousing.

You should be comfortable working with large datasets, designing scalable data pipelines, optimizing Spark workloads, building warehouse solutions, and troubleshooting production data environments.

Strong experience delivering enterprise data engineering solutions from development through production support will be highly valued.

Work Location

📍 Dallas, Texas

Onsite position.

Candidates should be prepared to work onsite in Dallas throughout the engagement.

Contract Duration & Employment

Duration: 12 Months
Employment: C2C Contract
Work Authorization: Any Visa Accepted

How to Apply

Qualified candidates with strong Databricks, PySpark, Python, Snowflake, Data Warehouse, ETL/ELT, and Data Engineering experience are encouraged to submit their updated resume.

📩 Share Resume:
krishna@vanguard-itsolutions.com

Please include your current location, total experience, visa/work authorization, Databricks experience, Snowflake experience, and availability when submitting your profile.