Our client is a 4-year-old, fast-growing, "Great Place to work" certified, Software and Services company with a growing team of 200+ professionals working across various cities in India and US.
Mission: They will build simple, scalable solutions using Blockchain, IoT and AI Technologies that enable their customers to realize unprecedented business value year after year.
Vision: They will become an advanced information technology company powered by happy, intellectual and extraordinarily capable people.
Job Description: Roles and Responsibilities: • Designs, develops, optimizes, and maintains data architecture and pipelines that adhere to Data Pipeline (ELT) principles and business goals. • Solves complex data problems to deliver insights that help the business achieve its goals. • Creates data products for engineers, analysts, and data scientist team members to accelerate their productivity. • Engineers effective features for modeling in close collaboration with data scientists and businesses. • Leads the evaluation, implementation, and deployment of emerging tools and processes for analytics data engineering to improve productivity and quality. • Partners with machine learning engineers, BI, and solutions architects to develop technical architectures for strategic enterprise projects and initiatives.
Requirements: • Bachelor's degree in computer science, statistics, engineering, or a related field. • 8-15 years of experience required. • Experience in PySpark is required for this position, with strong knowledge of Microsoft Fabric being a plus. • Experience designing and maintaining data warehouses and/or data lakes with big data technologies such as Spark/Databricks or distributed databases like Redshift and Snowflake. • Experience in housing, accessing, and transforming data in various relational databases. • Experience building data pipelines and deploying/maintaining them following modern Data Engineering best practices (e.g., DBT, Airflow, Spark, Python OSS Data Ecosystem). • Knowledge of Software Engineering fundamentals and software development tooling (e.g., Git, CI/CD, JIRA), with familiarity with the Linux operating system and the Bash/Z shell. • Experience with cloud database technologies (e.g., Azure) and developing solutions on cloud computing services and infrastructure in the data and analytics space. • Basic familiarity with BI tools (e.g., Alteryx, Tableau, Power BI, Looker). • Expertise in ELT and data analysis, primarily SQL. • Conceptual knowledge of data and analytics, such as dimensional modeling, reporting tools, data governance, and structured and unstructured data.