Data Engineer – PySpark-W2

Job Title: Data Engineer – PySpark

Location: Dallas, TX,USA

Work Mode: Hybrid – Onsite

Experience: 6+ Years

Job Description

We are looking for an experienced Data Engineer with strong hands-on expertise in PySpark to design, develop, and maintain scalable data engineering solutions.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using PySpark and Python.
• Build and optimize ETL/ELT workflows for processing large volumes of structured and unstructured data.
• Develop data transformation and data processing solutions using Apache Spark.
• Work with distributed data processing frameworks and big data technologies.
• Perform data cleansing, validation, integration, and transformation.
• Optimize Spark jobs for performance, scalability, and reliability.
• Collaborate with data architects, analysts, and other engineering teams.
• Troubleshoot data pipeline issues and ensure data quality and consistency.
• Support data lake and data warehouse solutions.

Required Skills

• 6+ years of experience in Data Engineering or related roles.
• Strong hands-on experience with PySpark and Python.
• Strong experience with Apache Spark and distributed data processing.
• Experience developing and maintaining ETL/ELT data pipelines.
• Strong SQL skills and experience working with large datasets.
• Knowledge of data warehousing and data lake concepts.
• Experience with data transformation, optimization, and performance tuning.
• Ability to work independently and collaboratively in a hybrid work environment.

Preferred Skills

• Experience with cloud platforms such as AWS, Azure, or GCP.
• Knowledge of Databricks, Delta Lake, or similar data platforms.
• Experience with Snowflake or other cloud data warehouses.
• Familiarity with Airflow or other workflow orchestration tools.
• Experience with CI/CD and data engineering best practices.

Interested candidates can share their updated resume to [email protected]