Senior Data Scientist – AI, Data Engineering & Intelligent Automation

Аналитика рынка

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Описание

Key Responsibilities Data Analytics/Pyspark/Azure data bricks Pipeline Design & Development: Build, monitor, and maintain robust, scalable batch and real-time ETL/ELT pipelines using PySpark, SQL, Delta Lake, and Auto Loader. Data Governance & Security: Enforce data access policies, row/column-level security, and lineage tracking using Databricks Unity Catalog to protect PII and maintain compliance. Orchestration & Workflow Automation: Schedule and orchestrate multi-task jobs using Databricks Workflows (Lakeflow Jobs) or external schedulers (e.g., Apache Airflow, Azure Data Factory) Data Quality Assurance: Define and integrate automated data quality rules, validation checks, and testing frameworks (e.g., Great Expectations, Delta Live Tables expectations) directly into pipelines Big Data handling: Design and implement scalable data ingestion, transformation, and processing pipelines. Automate data collection, validation, and integration workflows. Ensure data quality, reliability, and governance across the data ecosystem. Interface with diverse enterprise data sources including databases, APIs, cloud platforms, files, streaming systems, and third-party applications. Analyze structured and unstructured data to derive actionable insights and recommendations. Design experiments, evaluate data performance, and continuously improve solution effectiveness. Apply advanced analytics techniques to support business decision-making. Data Visualization & Business InsightsBuild intuitive

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