Tiger Analytics is seeking a Lead Data Engineer with expertise in Azure to manage complex data engineering initiatives. The role requires strong analytical skills and experience in leading data engineering teams.
Tiger Analytics is pioneering what AI and analytics can do to solve some of the toughest problems faced by organizations globally. We develop bespoke solutions powered by data and technology for several Fortune 100 companies. We have offices in multiple cities across the US, UK, India, and Singapore, and a substantial remote global workforce. We are expanding our Data Engineering practice and looking for Azure Data Engineers to join our growing team of analytics experts. The right candidate will have strong analytical skills and the ability to combine data from different sources and will strive for efficiency by aligning data systems with business goals. Requirements Below are the specifics. • Data Engineering Lead – 9+ years’ experience leading DE engagements • Strong program management experience, managing complex data engineering initiatives – stakeholder management, risk management, offshore coordination with 6-10 members DE team. • Strong in communication; both at executive as well as execution level • Primary Skill- Azure, Databricks, SQL, Python • Secondary Skill- On Prem to Cloud Migration • Proficiency in Python programming. • Proficiency in SQL queries • Experience building data pipelines using Azure stack • 2+ years of experience using Apache spark • Good working experience on Delta Lake and ETL processing • Prior experience of working in a Unix environment • Experience in harmonizing raw data into a consumer-friendly format using Azure Databricks • Experience extracting/querying/joining large data sets at scale • Experience building data ingestion pipelines using Azure Data Factory to ingest structured and unstructured data • Experience in data wrangling, advanced analytic modeling is preferred • Strong communication and organizational skills Benefits This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility. Tiger Analytics is pioneering what AI and analytics can do to solve some of the toughest problems faced by organizations globally. We develop bespoke solutions powered by data and technology for several Fortune 100 companies. We have offices in multiple cities across the US, UK, India, and Singapore, and a substantial remote global workforce. We are expanding our Data Engineering practice and looking for Azure Data Engineers to join our growing team of analytics experts. The right candidate will have strong analytical skills and the ability to combine data from different sources and will strive for efficiency by aligning data systems with business goals. Requirements Below are the specifics. • Data Engineering Lead – 9+ years’ experience leading DE engagements • Strong program management experience, managing complex data engineering initiatives – stakeholder management, risk management, offshore coordination with 6-10 members DE team. • Strong in communication; both at executive as well as execution level • Primary Skill- Azure, Databricks, SQL, Python • Secondary Skill- On Prem to Cloud Migration • Proficiency in Python programming. • Proficiency in SQL queries • Experience building data pipelines using Azure stack • 2+ years of experience using Apache spark • Good working experience on Delta Lake and ETL processing • Prior experience of working in a Unix environment • Experience in harmonizing raw data into a consumer-friendly format using Azure Databricks • Experience extracting/querying/joining large data sets at scale • Experience building data ingestion pipelines using Azure Data Factory to ingest structured and unstructured data • Experience in data wrangling, advanced analytic modeling is preferred • Strong communication and organizational skills Benefits This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.
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