Data Engineer 

Experience: 12+ Years
Location: Georgia

Position Overview

We are seeking a highly skilled Data Engineer with 12+ years of experience in designing, building, and maintaining scalable data platforms, pipelines, and architectures. The ideal candidate will have strong expertise in data warehousing, ETL/ELT development, big data technologies, cloud platforms, and data integration solutions. The candidate will work closely with data analysts, data scientists, and business stakeholders to deliver reliable and efficient data solutions that support business intelligence and analytics initiatives.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT processes.
• Build and optimize data architectures, data lakes, and data warehouses.
• Develop solutions for processing large volumes of structured and unstructured data.
• Integrate data from multiple sources, including databases, APIs, cloud services, and third-party applications.
• Ensure data quality, integrity, security, and governance across enterprise data platforms.
• Collaborate with data analysts, data scientists, and business teams to understand data requirements.
• Implement and maintain data models, schemas, and transformation logic.
• Optimize data workflows, query performance, and storage solutions.
• Develop and support real-time and batch data processing systems.
• Monitor data pipelines and troubleshoot production issues.
• Implement automation, monitoring, and CI/CD processes for data engineering workflows.
• Participate in architecture reviews and recommend improvements for scalability and performance.
• Maintain technical documentation and data lineage information.
• Mentor junior engineers and contribute to data engineering best practices.

Required Skills & Qualifications

• 12+ years of experience in Data Engineering, ETL Development, or related fields.
• Strong proficiency in SQL and database technologies such as Oracle, SQL Server, PostgreSQL, MySQL, or Snowflake.
• Hands-on experience with ETL/ELT tools such as Informatica, Talend, SSIS, DataStage, or AWS Glue.
• Strong programming skills in Python, Scala, Java, or Spark SQL.
• Experience with Big Data technologies such as Apache Spark, Hadoop, Hive, Kafka, and Databricks.
• Expertise in data warehousing concepts, dimensional modeling, and data architecture.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (Google Cloud Platform).
• Knowledge of cloud data services including Redshift, BigQuery, Synapse, Snowflake, or Azure Data Factory.
• Experience with real-time data streaming technologies and event-driven architectures.
• Familiarity with CI/CD pipelines, Git, and DevOps practices.
• Strong understanding of data governance, security, and compliance standards.
• Excellent analytical, troubleshooting, and communication skills.
• Experience working in Agile/Scrum environments.

Preferred Qualifications

• Experience with Databricks, Delta Lake, Apache Airflow, or similar modern data platforms.
• Knowledge of machine learning data pipelines and AI/ML integration.
• Cloud certifications such as AWS Data Analytics, Azure Data Engineer Associate, or Google Professional Data Engineer preferred.
• Experience in Banking, Healthcare, Insurance, Retail, or Financial Services domains is a plus.

Educational Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Data Science, Engineering, or related field.
• Master’s degree preferred.