Job
Description
Technoidentity is seeking an experienced Analytics Engineer who is passionate about building reliable data systems and shaping scalable analytics frameworks. You will work at the intersection of engineering, analytics, and business, enabling informed decisions through trusted metrics, we'll-designed data models, and collaborative impact. On a typical day, you will: Collaborate with cross-functional stakeholders to gather data requirements and plan deliverables. Architect and implement robust data models (eg, Minerva assets) supporting key business domains and investor-related insights. Maintain and evolve the metrics architecture (eg, Midas) for enterprise-wide reporting. Develop interactive dashboards in tools like Tableau or Superset to empower self-serve analytics. Build and optimize data pipelines using tools like Spark, Presto, and Airflow. Troubleshoot data issues and drive technical discussions for long-term architectural improvements. Mentor junior team members, ensuring high-quality output aligned with best practices. How you'll Make a Difference Develop Scalable Solutions : Design and maintain pipelines and metrics infrastructure using Spark, Presto, and Airflow. Champion Data Excellence : Lead best practices in data modeling , metric design, and adherence to enterprise data standards like Midas. Drive Collaborative Impact : Act as a data strategy partner across Engineering, Platform, and Business verticals. Innovate Reporting Practices : Enhance frameworks for experimental design, A/B testing, and predictive modelling . Lead Organizational Strategy : Support scalable architectural decisions and manage key data dependencies. Your Expertise 4-6 years of relevant experience in data engineering, analytics engineering, or similar roles. Expertise in distributed data processing systems (eg, Spark, Presto, PySpark ). Advanced SQL skills with a deep understanding of dimensional data modeling . Proficiency in Python for data scripting and automation (Scala experience is a plus). Experience with BI tools like Tableau or Superset for dashboard development. Familiarity with workflow orchestration tools such as Airflow. Strong problem-solving, communication, and stakeholder management skills. Preferred Qualifications Experience in cloud data platforms (AWS, Azure, Snowflake, Databricks). Understanding of data governance and data quality frameworks. Exposure to modern data stack tools and collaborative environments.
