Lead Data Engineer

Harnham

Houston (TX)

On-site

USD 160,000 - 200,000

Full time

14 days+

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Benefits offered by this job

Medical insurance

Vision insurance

401(k)

Job summary

A leading data consultancy firm is looking for a Lead Data Engineer in Houston, TX. This role involves architecting and implementing modern cloud-based data solutions while leading cloud data engineering practices. Candidates should have at least 5 years of data engineering experience, particularly with Databricks Lakehouse and AWS services. Competitive salary package includes a base of $160,000-$200,000 plus a 25% bonus.

Qualifications

5+ years of experience in data engineering.
Strong track record with Databricks Lakehouse.
Advanced proficiency in AWS cloud services.
Hands-on development using Python, SQL, and/or Scala.

Responsibilities

Architect and implement modern cloud-based data pipelines.
Lead efforts in Databricks Lakehouse environments.
Build robust integration pipelines using various tools.
Collaborate with teams to align infrastructure with business goals.

Skills

Data engineering

Leadership in cloud-native environments

Databricks Lakehouse

AWS cloud services

Python

SQL

CI/CD workflows

Communication skills

Education

Bachelor's or Master's degree in Computer Science, Engineering, or similar

Tools

Apache Spark

Kafka

Airflow

Fivetran

AWS (S3, EC2, RDS, Lambda)

Job description

This range is provided by Harnham. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$160,000.00/yr - $200,000.00/yr

Direct message the job poster from Harnham

Recruitment Consultant - Data Science | ML | AI

Title: Lead Data Engineer

Location: Houston, TX

Compensation: $160,000-$200,000 base + 25% bonus

Employment Type: 4 Days on-site

A fast-evolving organization is seeking a Lead Data Engineer to spearhead cloud-native data architecture efforts within a growing enterprise initiative. This is a highly visible technical leadership role, responsible for designing and scaling modern data platforms based on Databricks Lakehouse and Medallion Architecture principles.

You’ll serve as the technical authority across cloud data engineering practices, guide the transition away from legacy platforms, and lead a Data Management Community of Practice (CoP) to drive innovation across engineering and business teams.

What You’ll Do

Architect and implement modern, scalable cloud-based data pipelines across Bronze, Silver, and Gold lakehouse layers
Lead efforts in Databricks Lakehouse environments and design end-to-end ingestion, transformation, and optimization workflows
Build robust integration pipelines using tools such as Apache Spark, Kafka, Airflow, Fivetran, and native AWS services
Act as the primary facilitator of the data engineering CoP, promoting best practices, technical growth, and standards adoption
Collaborate cross-functionally with data science, analytics, and business stakeholders to align infrastructure to business goals
Optimize data governance, lineage, security, and quality in a high-scale, real-time environment
Provide architectural oversight, troubleshoot performance issues, and guide adoption of modern data tools and frameworks

What You Bring

5+ years of experience in data engineering, with leadership roles in cloud-native or lakehouse environments
Strong track record with Databricks Lakehouse, including Medallion layer implementation
Advanced proficiency in AWS cloud services (S3, EC2, RDS, Lambda) and big data tooling (Apache Spark, Kafka, Hadoop)
Hands-on development using Python, SQL, and/or Scala for production-grade pipelines
Familiarity with CI/CD workflows, modern DevOps for data, and structured data modeling
Experience leading or facilitating technical communities of practice is highly preferred
Excellent communication skills with strong executive presence
Bachelor's or Master's degree in Computer Science, Engineering, or similar
Certifications in Databricks, AWS, or DAMA CDMP are a plus