Senior Data Engineer

Overview

On Site
Depends on Experience
Contract - W2
Contract - 12 Month(s)
No Travel Required

Skills

Machine Learning (ML)
Python
SQL
Scala
Terraform
Stakeholder Engagement
Leadership
ELT
Databricks
DevOps
Google Cloud Platform
Data Lake
Data Science
Big Data
Apache Spark
Apache Kafka
Apache Hive
Apache Hadoop
Agile
Amazon Redshift
Data Governance

Job Details

Job Title: Senior Data Engineer (12+ Years Experience)

Location: [Houston, TX]

Employment Type: Contract (Only W2)

Job Summary:

We are seeking an experienced Senior Data Engineer with over 12 years of experience in designing, building, and optimizing large-scale data platforms and pipelines. The ideal candidate has deep expertise in data architecture, cloud data engineering (AWS/Azure/Google Cloud Platform), big data technologies, and modern data stack tools. You will lead the end-to-end delivery of data solutions, mentor junior engineers, and collaborate with cross-functional teams to support scalable analytics and machine learning initiatives.

Key Responsibilities:

  • Design and implement high-performance data pipelines and ETL/ELT frameworks using tools like Spark, Kafka, Airflow, and DBT.

  • Develop and maintain data lake and data warehouse architectures (e.g., Snowflake, Redshift, BigQuery, Databricks).

  • Build scalable, distributed systems for batch and real-time data processing.

  • Optimize data models for analytics and machine learning.

  • Collaborate with Data Scientists, Analysts, and DevOps to productionize data workflows.

  • Implement and enforce data governance, quality, lineage, and security best practices.

  • Lead code reviews, technical design sessions, and architecture decisions.

  • Mentor and guide junior data engineers and contribute to engineering standards and best practices.

Required Skills & Qualifications:

  • 12+ years of experience in data engineering, software development, or related roles.

  • Strong expertise in SQL, Python, Scala, or Java.

  • Hands-on experience with Apache Spark, Hadoop, Kafka, Hive, etc.

  • Solid experience with cloud platforms (AWS, Azure, or Google Cloud Platform) and cloud-native services (e.g., AWS Glue, EMR, Lambda).

  • Experience with data modeling, data warehousing, and schema design.

  • Deep understanding of CI/CD for data pipelines and infrastructure as code (Terraform, CloudFormation).

  • Proficient in version control systems (e.g., Git) and agile delivery methods.

  • Strong analytical and problem-solving skills.

Preferred Qualifications:

  • Experience with Snowflake, Databricks, or BigQuery.

  • Knowledge of containerization (Docker/Kubernetes) for data services.

  • Familiarity with data security and compliance (GDPR, HIPAA).

  • Exposure to machine learning pipelines or MLOps is a plus.

Education:

  • Bachelor's or Master s degree in Computer Science, Engineering, Data Science, or related field.

Nice to Have:

  • Certifications in AWS/Azure/Google Cloud Platform Data Engineering.

  • Leadership in open-source data projects or contributions to tech communities.

  • Excellent communication and stakeholder engagement skills.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.