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)
