Quantitative Data Engineer Jobs in Dallas, TX (NOW HIRING)

Job Title: Data Engineer
Location: Dallas, TX
Job Summary:

As a Databricks Lead, you will be a critical member of our data engineering team, responsible for designing, developing, and optimizing our data pipelines and platforms on Databricks, primarily leveraging AWS services. You will play a key role in implementing robust data governance with Unity Catalog and ensuring cost-effective data solutions. This role requires a strong technical leader who can mentor junior engineers, drive best practices, and contribute hands-on to complex data challenges.

Responsibilities:

* Databricks Platform Leadership:

  * Lead the design, development, and deployment of large-scale data solutions on the Databricks platform.

  * Establish and enforce best practices for Databricks usage, including notebook development, job orchestration, and cluster management.

  * Stay abreast of the latest Databricks features and capabilities, recommending and implementing improvements.

* Data Ingestion and Streaming (Kafka):

  * Architect and implement real-time and batch data ingestion pipelines using Apache Kafka for high-volume data streams.

  * Integrate Kafka with Databricks for seamless data processing and analysis.

  * Optimize Kafka consumers and producers for performance and reliability.

* Data Governance and Management (Unity Catalog):

  * Implement and manage data governance policies and access controls using Databricks Unity Catalog.

  * Define and enforce data cataloging, lineage, and security standards within the Databricks Lakehouse.

  * Collaborate with data governance teams to ensure compliance and data quality.

* AWS Cloud Integration:

  * Leverage various AWS services (S3, EC2, Lambda, Glue, etc.) to build a robust and scalable data infrastructure.

  * Manage and optimize AWS resources for Databricks workloads.

  * Ensure secure and compliant integration between Databricks and AWS.

* Cost Optimization:

  * Proactively identify and implement strategies for cost optimization across Databricks and AWS resources.

  * Monitor DBU consumption, cluster utilization, and storage costs, providing recommendations for efficiency gains.

  * Implement autoscaling, auto-termination, and right-sizing strategies to minimize operational expenses.

* Technical Leadership & Mentoring:

  * Provide technical guidance and mentorship to a team of data engineers.

  * Conduct code reviews, promote coding standards, and foster a culture of continuous improvement.

  * Lead technical discussions and decision-making for complex data engineering problems.

* Data Pipeline Development & Optimization:

  * Develop, test, and maintain robust and efficient ETL/ELT pipelines using PySpark/Spark SQL.

  * Optimize Spark jobs for performance, scalability, and resource utilization.

  * Troubleshoot and resolve complex data pipeline issues.

* Collaboration:

  * Work closely with data scientists, analysts, and other engineering teams to understand data requirements and deliver solutions.

  * Communicate technical concepts effectively to both technical and non-technical stakeholders.

Qualifications:

* Bachelor's or Master's degree in Computer Science, Data Engineering, or a related quantitative field.

* 7+ years of experience in data engineering, with at least 3+ years in a lead or senior role.

* Proven expertise in designing and implementing data solutions on Databricks.

* Strong hands-on experience with Apache Kafka for real-time data streaming.

* In-depth knowledge and practical experience with Databricks Unity Catalog for data governance and access control.

* Solid understanding of AWS cloud services and their application in data architectures (S3, EC2, Lambda, VPC, IAM, etc.).

* Demonstrated ability to optimize cloud resource usage and implement cost-saving strategies.

* Proficiency in Python and Spark (PySpark/Spark SQL) for data processing and analysis.

* Experience with Delta Lake and other modern data lake formats.

* Excellent problem-solving, analytical, and communication skills.

Added Advantage (Bonus Skills):

* Experience with Apache Flink for stream processing.

* Databricks certifications.

* Experience with CI/CD pipelines for Databricks deployments.

* Knowledge of other cloud platforms (Azure, GCP) is a plus.