About Us:
LTIMindtree is a global technology consulting and digital solutions company that enables enterprises across industries to reimagine business models, accelerate innovation, and maximize growth by harnessing digital technologies. As a digital transformation partner to more than 700+ clients, LTIMindtree brings extensive domain and technology expertise to help drive superior competitive differentiation, customer experiences, and business outcomes in a converging world. Powered by nearly 90,000 talented and entrepreneurial professionals across more than 30 countries, LTIMindtree — a Larsen & Toubro Group company — combines the industry-acclaimed strengths of erstwhile Larsen and Toubro Infotech and Mindtree in solving the most complex business challenges and delivering transformation at scale. For more information, please visit www.ltimindtree.com.
Role: Data Engineer
Location: Princeton, NJ/Boston, MA
Job Description:
Minimum 6 to 9 years with deep understanding of Databricks architecture and Apache Spark in Azure
· Design, develop, and optimize Spark-based data pipelines
· Collaborate with teams to align solutions with business needs
· Strong proficiency in SQL, Python and Spark, with hands-on experience developing ETL processes and data pipelines
· Must have good work experience in ADLS, ADF & Data processing in Azure cloud and other RDBMS/appliances
· Knowledge of Data Modelling techniques (Data Vault 2.0), dimensional modelling and data warehousing concepts
· Understanding of RBAC.
· Experience in Query Optimization techniques.
LTIMindtree is an equal opportunity employer that is committed to diversity in the workplace. Our employment decisions are made without regard to race, color, creed, religion, sex (including pregnancy, childbirth or related medical conditions), gender identity or expression, national origin, ancestry, age, family-care status, veteran status, marital status, civil union status, domestic partnership status, military service, handicap or disability or history of handicap or disability, genetic information, atypical hereditary cellular or blood trait, union affiliation, affectional or sexual orientation or preference, or any other characteristic protected by applicable federal, state, or local law, except where such considerations are bona fide occupational qualifications permitted by law.