
Transformative Data Architect
7 hours ago
We are seeking a highly skilled Senior Data Engineer to join our team. This role requires expertise in designing and developing scalable data analytics solutions.
- Data Pipeline Design & Development:
- Design and build robust, scalable, and high-quality data pipelines that support analytics and reporting needs.
- Integration of structured and unstructured data from various sources into data lakes and warehouses.
- Build and maintain scalable ETL/ELT pipelines for batch and streaming data using Azure Data Factory, Databricks, Snowflake, and Azure SQL Server.
- Collaborate with data scientists, analysts, and platform engineers to enable analytics and ML use cases.
- Design, develop, and optimize DBT models to support scalable data transformations.
- Cloud Platform Engineering:
- Operationalize data solutions on cloud platforms, integrating services like Azure, Snowflake, and third-party technologies.
- Manage environments, performance tuning, and configuration for cloud-native data solutions.
- Data Modeling & Architecture:
- Apply dimensional modeling, star schemas, and data warehousing techniques to support business intelligence and machine learning workflows.
- Collaborate with solution architects and analysts to ensure models meet business needs.
- Data Governance & Security:
- Ensure data integrity, privacy, and compliance through governance practices and secure schema design.
- Implement data masking, access controls, and metadata management for sensitive datasets.
- Collaboration & Agile Delivery:
- Work closely with cross-functional teams including product owners, architects, and business stakeholders to translate requirements into technical solutions.
- Participate in Agile ceremonies, sprint planning, and DevOps practices for continuous integration and deployment.
- 7+ years of data engineering or design experience designing, developing, and deploying scalable enterprise data analytics solutions.
- 5+ years of experience in ML Lifecycle using Azure Kubernetes service, Azure Container Instance service, Azure Data Factory, Azure Monitor, Azure DataBricks building datasets, ML pipelines, experiments, logging, and monitoring.
- 5+ years of experience in data engineering using Snowflake.
- Experience in designing, developing & scaling complex data & feature pipelines feeding ML models and evaluating their performance.
- Experience in building and managing streaming and batch inferencing.
- Proficiency in SQL and any one other programming language.
- Strong experience with cloud platforms and containerization technologies.
- Experience with CI/CD tools such as GitHub Actions, GitLab, Jenkins, or similar tools.
- Familiarity with security best practices in DevOps and ML Ops.
- Experience in developing and maintaining APIs.
- Agile/Scrum operating experience using Azure DevOps.
- Experience with MS Cloud - ML Azure Databricks, Data Factory, Synapse, among others.
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