Data Engineer

The ideal candidate will have a strong background in data engineering, with proficiency in ETL/ELT processes, big data technologies, and cloud platforms. You will play a critical role in ensuring data accessibility, quality, and scalability to support business intelligence, analytics, and operational objectives. This position offers an exciting opportunity to work collaboratively with cross-functional teams and leverage your expertise to shape our data infrastructure.

Responsibilities

• Design, develop, and implement scalable data pipelines to extract, transform, and load data from various sources.
• Build and maintain data warehouses and lakes to support business intelligence and analytics.
• Write high-quality code and conduct peer code reviews to ensure best practices.
• Develop data models and schemas for effective data analysis and reporting.
• Optimize data processing, query performance, and platform efficiency.
• Ensure data quality, integrity, and security through robust governance practices
• Lead the migration of legacy data platforms to Azure.
• Modernize applications and databases to leverage Azure's advanced capabilities.
• Implement monitoring solutions for database usage, performance, and reliability.
• Develop automated data quality checks and testing procedures.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 4+ years of experience in a similar role within the technology industry.
• Proven experience in data engineering, with a strong foundation in ETL/ELT processes and data warehousing.
• Proven ability to work with both OLTP (Postgres/MySQL) and OLAP systems (Redshift/Vertica/Snowflake).
• Hands-on experience in designing, optimizing, and managing batch and streaming data pipelines.
• Expertise in data migration and modernization, particularly on Azure cloud platforms.
• Microsoft Certification in Azure Data Engineering is highly desirable.
• Expertise in SQL, Python, and other programming languages relevant to data engineering.
• Experience with big data technologies such as Hadoop, Spark, and Hive.
• Knowledge and hands-on experience with cloud platforms like AWS, Azure, or GCP, including services such as Azure Data Factory, Azure Synapse Pipeline, Azure Event Hub, and Azure IoT Hub.
• Familiarity with data visualization tools like Tableau or Power BI.
• Knowledge of machine learning and statistical modelling is a plus.
• Onsite availability required

Benefits

• Private Health Insurance.
• Paid Time Off.
• Opportunities for Professional Growth and Career Advancement.
• Training and Development Programs.
• Competitive Salary.
• Collaborative and Supportive Work Environment.