Lead Data Platform Engineer

High Tech Genesis

$120K — $140K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 8+ years of data engineering experience, including 2+ years in a leadership position.
  • Proficient in Python, with expertise in Pandas, NumPy, and PySpark.
  • Hands-on experience with data processing frameworks like Hadoop and Databricks.
  • Advanced SQL skills and experience with both relational and distributed databases.
  • Familiarity with cloud platforms, particularly Azure or AWS, and tools like Databricks or Snowflake.
  • Knowledgeable in ETL/ELT tools such as Apache Airflow, Apache NiFi, or Azure Data Factory.
  • Experience in CI/CD and DevOps practices within enterprise data platforms.

Responsibilities

  • Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
  • Build and optimize data platforms using Hadoop, Databricks, and cloud technologies.
  • Integrate structured and semi-structured data into high-quality data solutions.
  • Collaborate with teams to convert business and analytics needs into engineering solutions.
  • Lead design discussions and advocate for best practices in data architecture.
  • Mentor data engineers while contributing to standards and platform scalability.
  • Drive innovation through proof-of-concepts and ongoing platform enhancements.

Benefits

  • Opportunities for mentoring and professional development.
  • Exposure to advanced tools and technologies in data engineering.
  • Collaborative and cross-functional team environment.
  • Innovative projects with a focus on continuous improvement.
  • Flexibility to support work-life balance.
Full Job Description
Overview

We are seeking a Lead Data Platform Engineer to design, build, and optimize scalable data platforms and pipelines that support enterprise analytics and data-driven solutions. This role combines hands-on engineering with technical leadership, driving best practices in data architecture, platform performance, and governance while mentoring engineering teams.

Key Responsibilities
  • Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
  • Build and optimize data platforms using Hadoop, Databricks, and cloud-based technologies.
  • Integrate structured and semi-structured data into reliable, high-quality data solutions.
  • Partner with cross-functional teams to translate business and analytics requirements into scalable engineering solutions.
  • Lead technical design discussions and promote best practices in data modeling, performance optimization, and governance.
  • Mentor data engineers and contribute to engineering standards, architecture, and platform scalability.
  • Support innovation through proof-of-concepts, automation, and continuous platform improvements.


  • 8+ years of experience in data engineering, including 2+ years in a technical leadership role.
  • Strong Python skills (Pandas, NumPy, PySpark) and experience with Impala.
  • Hands-on experience with Hadoop, Databricks, and large-scale data processing.
  • Advanced SQL and experience with relational and distributed databases.
  • Experience with cloud platforms such as Azure or AWS, including Databricks or Snowflake.
  • Strong knowledge of ETL/ELT tools such as Apache Airflow, Apache NiFi, or Azure Data Factory.
  • Experience with CI/CD, DevOps practices, and enterprise data platforms.
  • Understanding of data modeling, governance, and performance optimization.

Nice to Have
  • Experience supporting AI/GenAI solutions through scalable data pipelines.
  • Knowledge of machine learning workflows, feature engineering, and model serving.
  • Experience processing unstructured data and implementing data governance, privacy, and security best practices.
  • Strong analytical and problem-solving skills with the ability to communicate effectively across technical and business teams.

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