Data Engineering Manager

Full-time - Senior

Dallas, TX

Securities, Commodity Contracts, and Other Financial Investments and Related Activities

About the position

Join Our Team as a Data Engineer Manager. Are you passionate about driving impactful data solutions in dynamic industries like Oil & Gas, Financial Services, and Titles & Leases? We're seeking an experienced Data Engineering leader who thrives in crafting enterprise-level data strategies and managing modern, scalable data infrastructure. If you have a strong background in data engineering, expertise in cloud platforms, and a desire to work on cutting-edge AI/ML projects, this is the opportunity for you to shape the future of data at an innovative organization.

Responsibilities

• Establish Enterprise data strategy for ingestion, persistence, consumption, ETL/ELT, versioning for different data types e.g. relational, document, geospatial, graph, time series etc. in transactional and analytical patterns.
• Lead design and development of applications for data extraction, OCR, and data classification/categorization from various document formats (TIFF, PDF, etc.).
• Analyze and improve the efficiency, scalability, and reliability of our data infrastructure.
• Collaborate closely with Senior AI/ML Engineers to ensure seamless integration of data engineering and AI/ML models.
• Manage and scale data infrastructure on cloud platforms, leveraging cloud-native tools and services.
• Optimize the cost of data stores through an appropriate persistence, archival and retrieval, and purging strategies.
• Facilitate effective communication across teams, ensuring alignment and timely resolution of issues.
• Continuously evaluate and integrate new tools and technologies to keep our data solutions modern and efficient.
• Implement best practices in data management and engineering to continuously improve our processes.

Requirements

• A Bachelor's degree in Computer Science, Engineering (B.Tech, BE), or a related field such as MCA (Master of Computer Applications) is required.
• 12+ years in data engineering, including 5+ years in leading data teams.
• Prior experience in Oil & Gas, Titles & Leases, or Financial Services is a must have.
• Proficiency in Java, Python, or Scala with expertise in ETL/ELT processes, Databricks, Spark, and cloud platforms.
• AI/ML expertise especially in NLP and recent experience with Gen AI is highly desirable.
• Strong skills in data modeling, designing Data Lakehouses, and building scalable data pipelines.
• Experience with modern data stack, data orchestration, and workflow tools.
• Experience in processing, storing, and analyzing geospatial datasets, including vector and raster data formats.
• Proficiency in geospatial tools such as PostGIS, GDAL, GeoPandas, and spatial databases.
• Expertise in data governance, data quality, and data security practices.
• Proficiency in relational and NoSQL databases like PostgreSQL, MongoDB, Redis, and Elasticsearch.
• Experience with message queues like Kafka and stream processing.
• Strong expertise in SQL and experience with cloud data platforms such as Snowflake, Databricks, and BigQuery.
• Strong problem-solving skills with a focus on building scalable and reliable data infrastructure.
• Experience in delivering advanced data & analytics products and managing enterprise-level production data platforms.
• Experience with data visualization and BI tools. PowerBI expertise highly desirable.

Benefits

• Salary: Competitive and aligned with local standards.
• Performance Bonus: According to company policy.
• Benefits: Includes medical insurance and group term life insurance.
• Continuous learning and development.
• 10 recognized public holidays.
• Parental Leave.