Lead Data Engineer (AWS)

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Dallas / $165000 - $175000 annum

INFO

Salary
SALARY:

$165000 - $175000

Location

LOCATION

Dallas

Job Type
JOB TYPE

Permanent

Lead Data Engineer- AWS

Our client is looking for a Lead Data Engineer to lead the design, development, and optimization of a cloud-native data platform on AWS, driving migration from onpremises systems, building lakehouse and warehouse architectures, and enabling analytics and AI workloads. Mentor a team of engineers while remaining hands-on with data pipelines, orchestration, and cloud infrastructure.

*Applicants must be U.S. citizens; we are unable to provide sponsorship for this role.

This opportunity is Hybrid- based in Dallas OR Houston, TX

Responsibilities

  • Design, build, and optimize ETL/ELT pipelines using Python/PySpark, SQL, and AWS services (Glue, Redshift, Athena, S3, EMR, Lambda).
  • Lead data lakehouse/warehouse architecture using Iceberg, Parquet, and Lake Formation.
  • Implement workflow orchestration (Airflow, Step Functions) and CI/CD for data pipelines.
  • Drive data quality, governance, and security</strong>; implement monitoring, alerting, and incident-response frameworks.
  • Optimize compute, storage, and network usage</strong>; perform architecture reviews and tuning.
  • Mentor and guide a team of data engineers; enforce coding standards and best practices.
  • Collaborate with architects and stakeholders to define data models, integration patterns, and platform roadmaps.
  • Enable analytics and ML/AI pipelines by delivering scalable, reliable data products.

Qualifications

  • 5-7 years of hands-on data engineering; 3+ years in a technical lead role.
  • Strong AWS expertise: S3, Glue, Redshift, Athena, EMR/Spark, Lambda, IAM, Lake Formation.
  • Proficient in Python/PySpark or Scala and advanced SQL.
  • Experience with large-scale ETL/ELT pipelines, data lakes, lakehouses, and warehouses.
  • Expertise in data lakehouse architectures (Iceberg, Parquet) and orchestration (Airflow, Step Functions).
  • Knowledge of CI/CD, infrastructure-as-code (Terraform/CloudFormation), automated testing, and DevOps practices.
  • Strong understanding of data modeling, governance, security, and metadata management.
  • Experience designing pipelines to support ML/AI workloads.
  • Proven leadership and mentoring skills; able to drive engineering excellence.
  • AWS certifications (Data Analytics - Specialty or Solutions Architect) preferred.

U.S. work authorization required | Hybrid role (Dallas or Houston, TX)

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