Data Scientist Contractor

Description • As a Data Scientist Contractor, you will analyze complex data sets to extract meaningful insights and support data-driven decision-making. • Collect, process, and analyze large datasets to identify trends, patterns, and insights. • Develop and implement machine learning models and algorithms to solve business problems. • Create data visualizations and dashboards to communicate findings to stakeholders. • Collaborate with project teams to understand data requirements and deliver relevant analytical solutions. • Ensure data accuracy and integrity by performing data validation and quality checks. Primary Skill Required for the Role: • Databricks Architect Level Required for Primary Skill: • Advanced (6-9 years experience) Job Overview: We are seeking a skilled Data Engineer with hands-on Databricks experience to design, build, and optimize large-scale data pipelines and analytics solutions. You will work with cross-functional teams to enable scalable data processing using the Databricks Lakehouse Platform on Azure. Key Responsibilities: • Design and implement ETL/ELT pipelines using Databricks, Delta Lake, and Apache Spark • Collaborate with data scientists, analysts, and stakeholders to deliver clean, reliable, and well-modeled data • Build and manage data workflows with Databricks Jobs, Notebooks, and Workflows • Optimize Spark jobs for performance, reliability, and cost-efficiency • Maintain and monitor data pipelines, ensuring availability and data quality • Implement CI/CD practices for Databricks notebooks and infrastructure-as-code (e.g., Terraform, Databricks CLI) • Document data pipelines, datasets, and operational processes • Ensure compliance with data governance, privacy, and security policies Qualifications: • Bachelor’s or Master’s in Computer Science, Data Engineering, or a related field • 5+ years of experience in data engineering or a similar role • Strong hands-on experience with Databricks and Apache Spark (Python, Scala, or SQL) • Proficiency with Delta Lake, Unity Catalog, and data lake architectures • Experience with cloud platforms (Azure, AWS, or GCP), especially data services (e.g., S3, ADLS, BigQuery) • Familiarity with CI/CD pipelines, version control (Git), and job orchestration tools (Airflow, DB Workflows) • Strong understanding of data warehousing concepts, performance tuning, and big data processing Preferred Skills: • Experience with MLflow, Feature Store, or other machine learning tools in Databricks • Knowledge of data governance tools like Unity Catalog or Purview • Experience integrating BI tools (Power BI, Tableau) with Databricks • Databricks certification(s) (Data Engineer Associate/Professional, Machine Learning, etc.)