Offer summary

Qualifications:

Minimum of 5 years in data engineering or a related field., Proficiency in programming languages such as Python, Java, or Scala., Strong experience with data engineering frameworks like Apache Spark and Hadoop., Knowledge of database systems and cloud platforms such as AWS or Azure..

Key responsabilities:

Design, develop, and maintain scalable data pipelines and ETL processes.

Ensure data quality and integrity through robust testing and validation frameworks.

Collaborate with cross-functional teams to understand data requirements and deliver solutions.

Mentor and guide junior data engineers, fostering a culture of continuous learning.

Job description

*TEXAS BASED CANDIDATES ONLY*

Job Title: Senior Data Engineer

Overview: We are seeking an experienced Senior Data Engineer with a robust background in data engineering and a passion for technology. The ideal candidate will possess excellent problem-solving skills and the ability to lead and mentor junior engineers.

Experience:

Minimum of 5 years in data engineering or a related field.

Technical Skills:

Proficiency in programming languages such as Python, Java, or Scala.
Strong experience with data engineering frameworks and libraries (e.g., Apache Spark, Hadoop).
Expertise in designing and developing scalable and maintainable data pipelines and ETL processes.
Experience with version control systems (e.g., Git).
Familiarity with Agile development methodologies.
Knowledge of database systems (e.g., SQL, NoSQL) and data modeling.
Experience with cloud platforms (e.g., AWS, Azure, Google Cloud).
Proficiency in distributed data processing and big data technologies.

Soft Skills:

Excellent problem-solving and analytical skills.
Strong communication and collaboration skills.
Ability to work independently and as part of a team.
Proven ability to lead and mentor junior team members.

Preferred Qualifications:

Experience with data warehousing solutions (e.g., Redshift, BigQuery, Snowflake).
Knowledge of DevOps practices and tools (e.g., CI/CD pipelines, Terraform, Ansible).
Experience with data orchestration and workflow technologies (e.g., Apache Airflow, Prefect, Dagster).
Familiarity with containerization and orchestration (e.g., Docker, Kubernetes).
Understanding of data security and governance practices.
Experience with real-time data processing technologies (e.g., Apache Kafka, Kinesis).

Responsibilities:

Design, develop, and maintain scalable data pipelines and ETL processes.
Ensure data quality and integrity through robust testing and validation frameworks.
Collaborate with cross-functional teams to understand data requirements and deliver solutions.
Optimize data processing workflows for performance and cost-efficiency.
Mentor and guide junior data engineers, fostering a culture of continuous learning and improvement.
Stay updated with emerging technologies and industry best practices in data engineering.

Required profile