Responsibilities:

• Design, develop, and maintain data pipelines for ingesting, processing, and transforming data from various sources into actionable insights.
• Integrate data from disparate sources (databases, APIs, and files) into a unified data platform using ETL processes and data integration techniques.
• Design and implement data models, schemas, and data structures to support analytical queries, reporting, and business intelligence needs.
• Optimize database performance, query execution, and data processing workflows for efficiency, scalability, and reliability.
• Ensure data quality, integrity, and consistency through data validation, cleansing, deduplication, and error-handling mechanisms.
• Architect and implement data solutions on Azure cloud platforms, leveraging Azure services for data storage, processing, and analytics.
• Implement data security measures, encryption techniques, and access controls to protect sensitive data and ensure compliance with regulations (e.g., GDPR, HIPAA).
• Work closely with cross-functional teams, data scientists, analysts, and stakeholders to understand data requirements, provide data solutions, and communicate insights effectively.
• Document data processes, workflows, and best practices, and promote data governance standards, data lineage, and metadata management.
• Stay updated with emerging technologies, industry trends, and best practices in data engineering, cloud computing, and data analytics to drive innovation and continuous improvement.

Required Skills:

• Proficiency in writing complex SQL queries, stored procedures, and functions for data extraction, transformation, and analysis.
• Experience in database design, optimization, and management using SQL Server, Azure SQL Database, or other relational database systems.
• Knowledge of data modeling techniques, including entity-relationship diagrams, dimensional modeling, and data normalization, is needed to design efficient data structures.
• Familiarity with ETL (Extract, Transform, Load) processes and tools such as Azure Data Factory, SSIS (SQL Server Integration Services), or other data integration platforms.
• Hands-on experience with Azure cloud services, including Azure SQL Database, Azure Data Lake, Azure Synapse Analytics, Azure Databricks, Azure Cosmos DB, etc.
• Understanding of big data technologies like Hadoop, Spark, Kafka, and NoSQL databases for handling large-scale data processing and analytics.
• Knowledge of data warehousing concepts, methodologies, and tools for building and maintaining data warehouses or data marts.
• Proficiency in programming languages such as Python, R, Java, or Scala for data manipulation, analysis, and scripting tasks.
• Ability to create interactive dashboards, reports, and visualizations using tools like Power BI, Tableau, or similar BI platforms.
• Basic understanding of machine learning concepts and algorithms for data mining, predictive modeling, and statistical analysis.

Job Type

Payroll

Categories

Data Engineer (Software and Web Development)

Cloud Architects (Software and Web Development)

Database Administrator (Software and Web Development)

DevOps Engineers (Software and Web Development)

Data Scientist (Software and Web Development)

Must have Skills

• ETL(Extract, Transform, Load) - 5 Years
• Advanced
• Azure SQL DB - 4 Years
• Advanced
• Azure DataBricks - 1 Years
• Azure Synapse analytics - 1 Years
• Python - 5 Years
• Advanced
• Power BI - 5 Years
• Advanced
• SQL - 5 Years
• Advanced
• Azure Cloud Services - 5 Years
• Advanced
• Database Design - 5 Years
• Advanced