Data Engineer Lead Database (Mongo, SQL),
Job Location:
Job Location:
Atlanta, GA - USA
Monthly Salary:
Not Disclosed
Monthly Salary:
Posted on:
13 days ago
Posted on:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Job Description - Data Engineering Tech Lead (7-10 Years Experience)
Role Overview We are seeking an experienced Data Engineering Tech Lead with 7-10 years of experience to design build and lead scalable data engineering solutions across enterprise platforms. The ideal candidate will be responsible for architecting data pipelines leading engineering teams collaborating with business and cross-functional IT teams and delivering high-quality data platforms analytics and reporting solutions. Key Responsibilities Data Engineering & Architecture Design develop and maintain scalable ETL/ELT pipelines and data workflows Build robust data ingestion frameworks for structured and unstructured data sources Architect and implement data lakes data warehouses and data marts Ensure high performance scalability and reliability of data systems Pipeline & Data Platform Development Develop and optimize batch and real-time data processing pipelines Work with modern tools such as Airflow AWS Glue Azure Data Factory PySpark or equivalent Implement data validation monitoring and quality frameworks Enable integration across upstream and downstream systems Database & Data Modeling Design and maintain SQL and NoSQL databases (e.g. MongoDB relational systems) Develop complex SQL queries stored procedures and performance tuning strategies Implement data models (dimensional star/snowflake schemas) Ensure data consistency integrity and governance Cloud & Data Ecosystem Design and manage cloud-based data platforms (AWS / Azure / GCP) Implement CI/CD pipelines for data engineering workflows Ensure availability scalability and reliability of data environments Leadership & Technical Mentoring Lead and mentor a team of Data Engineers and Developers Provide guidance on best practices coding standards and performance optimization Conduct code reviews design reviews and technical decision-making Foster a culture of continuous improvement and innovation Agile Delivery & Stakeholder Collaboration Work within Scrum/Agile teams participating in sprint planning reviews and retrospectives Collaborate with Product Owners Business Analysts and Architects Work closely with cross-functional IT teams to deliver end-to-end data solutions Translate business needs into technical data solutions and architecture designs Data Quality Governance & Compliance Implement frameworks for data quality validation and monitoring Ensure compliance with enterprise data governance and security standards Support regulatory and audit requirements where applicable Required Skills & Experience 7-10 years of experience in Data Engineering / Data Platforms Strong expertise in: SQL and NoSQL databases (e.g. MongoDB) ETL/ELT pipelines and data integration Data warehousing and data modeling concepts Experience with big data and distributed systems (Spark Hadoop etc.) Hands-on experience with cloud platforms (AWS/Azure/GCP) Experience with workflow orchestration tools (Airflow ADF etc.) Strong knowledge of CI/CD and DevOps for data pipelines Proven experience in leading and mentoring engineering teams Preferred Skills Experience in Healthcare / Insurance / Data Analytics platforms Exposure to real-time streaming frameworks (Kafka Kinesis etc.) Experience in data governance and data quality frameworks Familiarity with API integrations and microservices architecture
Role Overview We are seeking an experienced Data Engineering Tech Lead with 7-10 years of experience to design build and lead scalable data engineering solutions across enterprise platforms. The ideal candidate will be responsible for architecting data pipelines leading engineering teams collaborating with business and cross-functional IT teams and delivering high-quality data platforms analytics and reporting solutions. Key Responsibilities Data Engineering & Architecture Design develop and maintain scalable ETL/ELT pipelines and data workflows Build robust data ingestion frameworks for structured and unstructured data sources Architect and implement data lakes data warehouses and data marts Ensure high performance scalability and reliability of data systems Pipeline & Data Platform Development Develop and optimize batch and real-time data processing pipelines Work with modern tools such as Airflow AWS Glue Azure Data Factory PySpark or equivalent Implement data validation monitoring and quality frameworks Enable integration across upstream and downstream systems Database & Data Modeling Design and maintain SQL and NoSQL databases (e.g. MongoDB relational systems) Develop complex SQL queries stored procedures and performance tuning strategies Implement data models (dimensional star/snowflake schemas) Ensure data consistency integrity and governance Cloud & Data Ecosystem Design and manage cloud-based data platforms (AWS / Azure / GCP) Implement CI/CD pipelines for data engineering workflows Ensure availability scalability and reliability of data environments Leadership & Technical Mentoring Lead and mentor a team of Data Engineers and Developers Provide guidance on best practices coding standards and performance optimization Conduct code reviews design reviews and technical decision-making Foster a culture of continuous improvement and innovation Agile Delivery & Stakeholder Collaboration Work within Scrum/Agile teams participating in sprint planning reviews and retrospectives Collaborate with Product Owners Business Analysts and Architects Work closely with cross-functional IT teams to deliver end-to-end data solutions Translate business needs into technical data solutions and architecture designs Data Quality Governance & Compliance Implement frameworks for data quality validation and monitoring Ensure compliance with enterprise data governance and security standards Support regulatory and audit requirements where applicable Required Skills & Experience 7-10 years of experience in Data Engineering / Data Platforms Strong expertise in: SQL and NoSQL databases (e.g. MongoDB) ETL/ELT pipelines and data integration Data warehousing and data modeling concepts Experience with big data and distributed systems (Spark Hadoop etc.) Hands-on experience with cloud platforms (AWS/Azure/GCP) Experience with workflow orchestration tools (Airflow ADF etc.) Strong knowledge of CI/CD and DevOps for data pipelines Proven experience in leading and mentoring engineering teams Preferred Skills Experience in Healthcare / Insurance / Data Analytics platforms Exposure to real-time streaming frameworks (Kafka Kinesis etc.) Experience in data governance and data quality frameworks Familiarity with API integrations and microservices architecture
