Analytix Business Solutions - Data Engineer

Job Description

Description About Analytix : Businesses of all sizes are faced with a rapidly changing competitive environment. Companies that possess both the ability to successfully navigate obstacles and the agility to react to market conditions are better positioned for long-term success. Analytix Solutions helps your company tackle these types of challenges. We empower business owners to confidently make informed decisions and positively impact profitability. We are a single-source provider of integrated solutions across multiple functional areas and disciplines. Through a combination of cross-disciplinary expertise, technological aptitude, and deep domain experience, we support our clients with efficient systems and processes, reliable data, and industry insights. We are your partner in strategically scaling your business for growth. Job Responsibilities Design, build, and maintain scalable, high-performance data pipelines and ETL/ELT processes across diverse database platforms. Architect and optimize data storage solutions to ensure reliability, security, and scalability. Leverage generative AI tools and models to enhance data engineering workflows, drive automation, and improve insight generation. Collaborate with cross-functional teams (Data Scientists, Analysts, and Engineers) to understand and deliver on data requirements. Develop and enforce data quality standards, governance policies, and monitoring systems to ensure data integrity. Qualifications Bachelor's or Masters degree in Computer Science, Information Technology, or a related field. 58 years of experience in data engineering, designing and managing large-scale data systems. Strong expertise in database technologies, including : SQL Databases : PostgreSQL, MySQL, SQL Server NoSQL Databases : MongoDB, Cassandra Data Warehouse/ Unified Platforms : Snowflake, Redshift, BigQuery, Microsoft Fabric. Experience with ETL tools (e.g., Apache Airflow, MS Fabric, Informatica, Talend) and data pipeline orchestration platforms. Strong understanding of data architecture, data modeling, and data governance principles. Experience with cloud platforms (preferably Azure). (ref:hirist.tech)