Senior Data Engineer

Job Title: Senior Data Engineer
Duration: 12 Months
Location: Dallas, TX / Remote
Type: Full-time W2 Only
Position Summary
We are seeking a highly skilled and results-driven Senior Data Engineer with 6+ years of experience designing, developing, and maintaining scalable data pipelines and cloud-based data solutions. The ideal candidate will work closely with business stakeholders, data analysts, data scientists, and software engineering teams to build reliable data infrastructure, optimize data processing workflows, and enable data-driven decision-making across the organization.
Local candidates are preferred. Candidates residing within commuting distance of the project location will be given preference.
Key Responsibilities
• Design, develop, and maintain scalable ETL/ELT pipelines to ingest, process, and transform structured and unstructured data from multiple sources.
• Build and optimize cloud-based data platforms and data warehouses to support reporting, analytics, and machine learning initiatives.
• Develop, optimize, and maintain complex SQL queries, stored procedures, and database objects for efficient data processing.
• Design and implement scalable data models, data lakes, and enterprise data warehouse solutions.
• Collaborate with business analysts, data scientists, and application teams to understand data requirements and deliver high-quality data solutions.
• Develop real-time and batch data processing pipelines using modern data engineering frameworks.
• Ensure data quality by implementing validation rules, monitoring processes, and automated error detection mechanisms.
• Optimize data pipeline performance, troubleshoot production issues, and improve overall system reliability and scalability.
• Implement data governance, metadata management, data lineage, and security best practices.
• Develop and maintain workflow orchestration using scheduling and automation tools.
• Support CI/CD deployment processes for data engineering solutions and automate operational tasks.
• Document data architectures, ETL processes, technical specifications, and operational procedures.
• Work closely with DevOps, cloud engineering, and infrastructure teams to deploy and maintain enterprise data platforms.
• Participate in Agile ceremonies including sprint planning, backlog grooming, daily stand-ups, sprint reviews, and retrospectives.
Required Qualifications
• Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, Mathematics, or a related field.
• 6+ years of experience as a Data Engineer, Big Data Engineer, ETL Developer, or Data Platform Engineer.
• Strong experience designing and developing ETL/ELT pipelines using tools such as Informatica, Azure Data Factory, AWS Glue, Apache Airflow, or similar technologies.
• Advanced proficiency in SQL and strong programming experience in Python, Scala, or Java.
• Experience working with cloud platforms including AWS, Microsoft Azure, or Google Cloud Platform.
• Hands-on experience with big data technologies such as Apache Spark, Hadoop, Kafka, Databricks, or Snowflake.
• Strong understanding of relational databases, NoSQL databases, data warehousing, dimensional modeling, and data lake architectures.
• Experience with version control systems such as Git and CI/CD deployment pipelines.
• Strong analytical, problem-solving, and troubleshooting skills.
• Excellent verbal and written communication skills with the ability to collaborate across cross-functional teams.
• Experience translating business requirements into scalable data engineering solutions.