Data & Analytics Lead Engineer (Big Data and Azure)
Since 1993, EPAM Systems, Inc. (NYSE: EPAM) has leveraged its advanced software engineering heritage to become the foremost global digital transformation services provider – leading the industry in digital and physical product development and digital platform engineering services. Through its innovative strategy; integrated advisory, consulting and design capabilities; and unique ‘Engineering DNA,EPAM’s globally deployed hybrid teams help make the future real for clients and communities around the world by powering better enterprise, education and health platforms that connect people, optimize experiences, and improve people’s lives. Selected by Newsweek as a 2021 Most Loved Workplace.
EPAM’s global multi-disciplinary teams serve 61,300 employees and customers in more than 50 countries across five continents.
As a recognized leader, EPAM is listed among the top 15 companies in Information Technology Services on the Fortune 1000 and ranked as the top IT services company on Fortune’s 100 Fastest-Growing Companies list for the last three consecutive years.
EPAM is also listed among Ad Age’s top 25 World’s Largest Agency Companies and in 2020, Consulting Magazine named EPAM Continuum a top 20 Fastest-Growing organization.
- 8 to 12 years in Big Data & Data related technology experience
- Expert level understanding of distributed computing principles
- Expert level knowledge and experience in Apache Spark
- Hands on experience in Azure – Databricks, Data Factory, Data Lake store/Blob storage, SQL DB
- Experience in creating Big data Pipelines with Azure components
- Hands on programing with Python
- Proficiency with Hadoop v2, Map Reduce, HDFS, Sqoop
- Experience with building stream-processing systems, using technologies such as Apache Storm or Spark-Streaming
- Experience with messaging systems, such as Kafka or RabbitMQ
- Good understanding of Big Data querying tools, such as Hive, and Impala
- Experience with integration of data from multiple data sources such as RDBMS (SQL Server, Oracle), ERP, Files
- Good understanding of SQL queries, joins, stored procedures, relational schemas
- Experience with NoSQL databases, such as HBase, Cassandra, MongoDB
- Knowledge of ETL techniques and frameworks
- Performance tuning of Spark Jobs
- Experience with designing and implementing Big data solutions
- Practitioner of AGILE methodology
- Big Data
- Azure Databricks
- Azure Data factory
can't find the job you are looking for?
Send us your CV to get a personalized offer.