Lead Data Engineer

Job Title: Lead Data Engineer

Duration: Direct Hire

Location: Dallas, TX (100% On-Site)

We are seeking a highly skilled and experienced Lead Data Engineer to join our dynamic team. The ideal candidate will have a strong background in data engineering, data warehousing, and cloud platforms. This role will involve leading the design and development of robust data pipelines, streaming ingestion frameworks, and scalable data architectures to support our data-driven initiatives. You will collaborate closely with cross-functional teams to ensure data integrity, availability, and accessibility across the organization.

Key Responsibilities:

Lead the design, development, and maintenance of scalable data pipelines, ETL/ELT processes, and data models.

Focus on Kafka, HDFS, HBase, Parquet, Spark, and Flink to ensure efficient data ingestion, storage, and processing.

Build and manage data ingestion frameworks using big data technologies, ensuring high efficiency and reliability.

Develop and optimize data storage solutions, including data warehousing, data lakes, and NoSQL databases on cloud platforms such as AWS, Azure, or Google Cloud.

Collaborate with data scientists, analysts, and business stakeholders to understand data needs and deliver solutions that meet those needs.

Ensure data quality, governance, and security through the implementation of best practices and robust monitoring systems.

Work with various data formats, including Parquet, Avro, and others, to ensure efficient data processing and storage.

Mentor and provide technical leadership to junior data engineers, fostering a culture of continuous learning and improvement.

Qualifications:

Bachelor's degree in Computer Science, Engineering, or a related field; Master's degree .

3+ years of proven experience as a Data Engineer or in a similar role, with a strong focus on data warehousing, ETL/ELT processes, and data modeling.

Proficiency in programming such as Python, Java, or Scala.

Hands-on experience with big data technologies such as Kafka, Spark, HDFS, HBase, Flink, DBT, SQLMesh, etc.

Experience with cloud platforms such as AWS, Azure, or Google Cloud.

Strong SQL skills and experience working with both relational and NoSQL databases.

Familiarity with data visualization tools such as Tableau, Power BI, or Looker.

Excellent problem-solving and analytical skills.

Strong communication and collaboration skills, with the ability to work effectively in a team environment.

Qualifications:

Experience with building and managing data pipelines in a multi-cloud environment.

Familiarity with data governance and data quality frameworks.

Experience in mentoring or leading a team of data engineers.