Senior Data , BI & AI Enablement Engineer

· Ensures data consistency and integrity during the integration process, performing data validation and cleaning as needed.

· Transforms raw data into a usable format by applying data cleansing, aggregation, filtering, and enrichment techniques.

· Optimizes data pipelines and data processing workflows for performance, scalability, and efficiency.

· Monitors and tunes data systems, identifies and resolves performance bottlenecks, and implements caching and indexing strategies to enhance query performance

· Implements data quality checks and validations within data pipelines to ensure the accuracy, consistency, and completeness of data.

· Manage Databricks Unity Catalog including administrative activities (policies, security, access control, cost control).

· Optimize and administer Databricks environments to ensure high performance and reliability.

· Cluster configuration and policy management in Databricks.

· Build and maintain CI/CD pipelines (DevOps) in GitHub or Azure DevOps.

· Collaborate with cross-functional teams to deliver comprehensive data solutions.

· Ensure data quality, security, and governance across all data processes.

· Communicate effectively with stakeholders to understand requirements and deliver actionable insights.

· Operate within agile teams, contributing to continuous improvement in data engineering practices and processes.

· Utilize cloud platforms such as AWS and Azure to build scalable data solutions.

· Collaborates with data scientists and data analysts to optimize models and algorithms for data quality, security, and governance.

Job Requirements

Education:

• A bachelor’s degree in computer science, data science, software engineering, information systems, information technology or related quantitative field; master’s degree preferred.

Experience:

· Minimum of 6+ yrs of experience in data engineering, with at least 2+ yrs of hands-on experience with Databricks.

· At least 6+ yrs of work experience in data management disciplines, including data integration, modeling, optimization and data quality, or other areas directly relevant to data engineering responsibilities and tasks.

Skills

· Databricks Certifications (Associate, Professional, Administration).

· Proficiency in modern data modeling techniques and data administration.

· Strong knowledge of SQL, Python, PySpark.

· Experience with cloud platforms such as AWS and Azure.

· Expert problem-solving skills, including debugging skills, allowing the determination of sources of issues in unfamiliar code or systems, and the ability to recognize and solve repetitive problems.

· Strong communication skills and a proactive, “getting things done” mindset.

· Experience working in agile teams and familiarity with agile methodologies.

· Ability to design, build, and deploy data solutions that capture, explore, transform, and utilize data to support AI, ML, and BI.

· Proficiency in the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure, GCP) and modern data warehouse tools (Snowflake, Databricks).

· Experience with database technologies such as SQL, NoSQL, Oracle, Hadoop, or Teradata.

· Ability to collaborate within and across teams of different technical knowledge to support delivery and educate end users on data products.

· Excellent business acumen and interpersonal skills; able to work across business lines at a senior level to influence and effect change to achieve common goals.

· Ability to describe business use cases/outcomes, data sources and management concepts, and analytical approaches/options.

· Ability to translate among the languages used by executive, business, IT, and quant stakeholders.

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