TalTeam
Key Responsibilities
Design and implement conceptual, logical, and physical data models within the Databricks Lakehouse on AWS, optimized for analytics, cost, and performance. Collaborate with product owners, architects, data engineers, and vendors to build data structures that support query optimization, storage efficiency, and compute performance. Define and govern Bronze, Silver, and Gold layers of the Lakehouse model, establishing best practices for data ingestion, transformation, and curation. Develop ELT pipelines using Databricks and Spark to integrate data from diverse sources (e.g., APIs, relational databases, files) while ensuring quality and lineage. Optimize Databricks workflows and SQL/Spark code using caching, partitioning, and clustering to improve scalability and reduce costs. Implement data governance and security controls in compliance with FedRAMP, FISMA, and federal security policies to ensure data integrity, confidentiality, and traceability. Document metadata, data definitions, and lineage using data dictionaries and model artifacts. Support basic data visualization efforts using tools such as Tableau to assist reporting and analytics teams. Qualifications:
10+ years of experience in data modeling, AI/data science, or software engineering with expertise in large-scale data systems. Bachelor's degree in Computer Science, Information Systems, or related field (or equivalent work experience). Expert-level proficiency in Databricks on AWS, including Databricks SQL, Runtime, clusters, notebooks, and data integrations. Hands-on experience with Spark (Python/Scala) and complex SQL for data transformation and aggregation. Deep knowledge of ETL/ELT development, data pipeline architecture, and performance tuning. Familiarity with cloud architecture, AWS data services, and security frameworks within government cloud environments. Strong understanding of data governance, quality, and lineage tracking principles. Preferred Certifications:
Databricks Certified Data Engineer Associate/Professional AWS Certified Data Analytics - Specialty Equivalent certifications in data modeling, cloud, or data governance
**Talteam Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.**
Design and implement conceptual, logical, and physical data models within the Databricks Lakehouse on AWS, optimized for analytics, cost, and performance. Collaborate with product owners, architects, data engineers, and vendors to build data structures that support query optimization, storage efficiency, and compute performance. Define and govern Bronze, Silver, and Gold layers of the Lakehouse model, establishing best practices for data ingestion, transformation, and curation. Develop ELT pipelines using Databricks and Spark to integrate data from diverse sources (e.g., APIs, relational databases, files) while ensuring quality and lineage. Optimize Databricks workflows and SQL/Spark code using caching, partitioning, and clustering to improve scalability and reduce costs. Implement data governance and security controls in compliance with FedRAMP, FISMA, and federal security policies to ensure data integrity, confidentiality, and traceability. Document metadata, data definitions, and lineage using data dictionaries and model artifacts. Support basic data visualization efforts using tools such as Tableau to assist reporting and analytics teams. Qualifications:
10+ years of experience in data modeling, AI/data science, or software engineering with expertise in large-scale data systems. Bachelor's degree in Computer Science, Information Systems, or related field (or equivalent work experience). Expert-level proficiency in Databricks on AWS, including Databricks SQL, Runtime, clusters, notebooks, and data integrations. Hands-on experience with Spark (Python/Scala) and complex SQL for data transformation and aggregation. Deep knowledge of ETL/ELT development, data pipeline architecture, and performance tuning. Familiarity with cloud architecture, AWS data services, and security frameworks within government cloud environments. Strong understanding of data governance, quality, and lineage tracking principles. Preferred Certifications:
Databricks Certified Data Engineer Associate/Professional AWS Certified Data Analytics - Specialty Equivalent certifications in data modeling, cloud, or data governance
**Talteam Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.**