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Lead Data Engineer

  • Lead Data Engineer job type Posted on: Oct 25, 2026
  • Lead Data Engineer experience level Openkyber
  • Lead Data Engineer employment type Atlanta, Georgia
  • Lead Data Engineer employment type Onsite
  • Lead Data Engineer salary Full-time

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Job Title :

Lead Data Engineer

Job Type :

Full-Time

Job Location :

Atlanta Georgia United States

Remote :

No

Jobcon Logo Job Description :

Position : Principal Lead Data Engineer (Snowflake, AWS services, Python, Control-M,IBM DataStage, SQL, CI/CD. Operation) : CTH/FTE : Visa Independent : Local to Detroit MI : Only USA Location : Detroit MI (Onsite & Local Needed) Type of Job : CTH/FTE Experience : 15+ Years Required Technical Skills
Snowflake: Strong expertise in Snowflake architecture, SQL development, performance tuning, security/roles, data loading/unloading, and best practices.
AWS: Hands-on experience with AWS data ecosystem (commonly S3, IAM, CloudWatch; plus services such as Glue, Lambda, EC2, Step Functions, EMR, or Kinesis as applicable).
Python: Strong Python programming for data engineering (ETL/ELT frameworks, API ingestion, automation, unit testing, logging).
Control-M: Experience designing and managing enterprise job scheduling, dependencies, calendars, SLAs, monitoring, and incident handling.
IBM DataStage: Solid experience building and maintaining DataStage jobs, handling complex transformations, and supporting production workloads.
SQL: Advanced SQL skills for transformations, optimization, and data validation across large datasets.
CI/CD & Version Control: Experience with Git and CI/CD practices for data pipelines (tools may vary).
Operational Excellence: Monitoring, alerting, and production support experience in a 24x7 or business-critical environment.
Good to Have AI/ML exposure: Experience enabling AI/ML pipelines or feature datasets; familiarity with ML lifecycle concepts, feature engineering, or MLOps tools/processes.
Experience with data governance/metadata tools and practices (catalog, lineage, data quality frameworks).
Exposure to streaming or event-driven architectures.
Required Soft Skills
  • Strong experience working in Agile/Scrum teams and delivering within structured SDLC processes.
  • Excellent communication skills (technical and non-technical) with the ability to explain complex data concepts clearly.
  • Proven ability to coordinate across multiple teams (Data Engineering, Data Science, DevOps, Security, BI, and business stakeholders).
  • Strong ownership mindset, problem-solving ability, and attention to detail.

Qualifications (Typical)

Bachelor s degree in Computer Science, Engineering, or related field (or equivalent practical experience). 9+ years of data engineering experience, including enterprise-grade data platform delivery and production support.

For applications and inquiries,

Jobcon Logo Position Details

Posted:

Oct 25, 2026

Reference Number:

95930-38381

Employment:

Full-time

City:

Atlanta

Job Origin:

CIEPAL_ORGANIC_FEED

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Position : Principal Lead Data Engineer (Snowflake, AWS services, Python, Control-M,IBM DataStage, SQL, CI/CD. Operation) : CTH/FTE : Visa Independent : Local to Detroit MI : Only USA Location : Detroit MI (Onsite & Local Needed) Type of Job : CTH/FTE Experience : 15+ Years Required Technical Skills
Snowflake: Strong expertise in Snowflake architecture, SQL development, performance tuning, security/roles, data loading/unloading, and best practices.
AWS: Hands-on experience with AWS data ecosystem (commonly S3, IAM, CloudWatch; plus services such as Glue, Lambda, EC2, Step Functions, EMR, or Kinesis as applicable).
Python: Strong Python programming for data engineering (ETL/ELT frameworks, API ingestion, automation, unit testing, logging).
Control-M: Experience designing and managing enterprise job scheduling, dependencies, calendars, SLAs, monitoring, and incident handling.
IBM DataStage: Solid experience building and maintaining DataStage jobs, handling complex transformations, and supporting production workloads.
SQL: Advanced SQL skills for transformations, optimization, and data validation across large datasets.
CI/CD & Version Control: Experience with Git and CI/CD practices for data pipelines (tools may vary).
Operational Excellence: Monitoring, alerting, and production support experience in a 24x7 or business-critical environment.
Good to Have AI/ML exposure: Experience enabling AI/ML pipelines or feature datasets; familiarity with ML lifecycle concepts, feature engineering, or MLOps tools/processes.
Experience with data governance/metadata tools and practices (catalog, lineage, data quality frameworks).
Exposure to streaming or event-driven architectures.
Required Soft Skills

  • Strong experience working in Agile/Scrum teams and delivering within structured SDLC processes.
  • Excellent communication skills (technical and non-technical) with the ability to explain complex data concepts clearly.
  • Proven ability to coordinate across multiple teams (Data Engineering, Data Science, DevOps, Security, BI, and business stakeholders).
  • Strong ownership mindset, problem-solving ability, and attention to detail.

Qualifications (Typical)

Bachelor s degree in Computer Science, Engineering, or related field (or equivalent practical experience). 9+ years of data engineering experience, including enterprise-grade data platform delivery and production support.

For applications and inquiries,

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