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Job Description & How to Apply Below
Key Responsibilities
Design, implement, and maintain enterprise-level data architectures including data warehouses, data lakes, and lake houses.
Lead the data engineering efforts, including ETL/ELT processes, data pipelines, and workflow orchestration.
Develop conceptual, logical, and physical data models for complex business domains.
Ensure data governance, security, and compliance across all data assets.
Optimize data solutions for performance, scalability, and cost-efficiency.
Collaborate with business stakeholders to translate requirements into robust data solutions.
Evaluate and recommend new technologies, tools, and frameworks for data engineering and analytics.
Required Skills & Expertise
Strong experience in data engineering, data modeling, and database design.
Expertise in SQL, Python, Spark, or Scala for data processing.
Hands-on experience with cloud platforms (Azure, AWS, GCP) and their data services.
Experience with modern data warehousing/lakehouse technologies (Snowflake, Databricks, Synapse, MS Fabric, etc.).
Knowledge of ETL/ELT pipelines, data integration, and workflow orchestration.
Familiarity with big data ecosystems (Hadoop, Hive, Kafka) is a plus.
Strong understanding of data governance, metadata management, and security standards.
Excellent problem-solving, analytical, and communication skills.
Preferred Qualifications
Certifications in cloud platforms or data technologies.
Experience in real-time data processing and analytics.
Exposure to BI tools such as Power BI, Tableau, or Looker.
(t.tech)
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