Bigdata Engineer -Spark

About Us We are a decision science organization assisting clients to leverage their under-utilized data in making complex business decisions successfully. We comprise of Data Enthusiasts (engineers, scientists visualizers), Business Consultants, and Sales Managers with a core focus to address your business growth via data. The most unique aspect of Data would be containing unique problems/opportunities even for organizations in the same sector. Since Marktine’s inception, we have worked with several sectors across Industries. We are still growing and consistently striving to improve to deliver world-class Data Assessment & Management Services. We do not follow a complex process rather strive to make complex data terminologies as simple as possible for our clients. From the team’s perspective, we adhere to complete industry standards following proper work-life balance among employees and provide the knowledge space for improvement. We encourage team building and follow a culture of innovation, transparency, and integrity. We are always open for the right enthusiasts to join our team. Job Description This is a remote position. Responsibilities: As a developer, possess excellent Knowledge of distributed computing architecture, core hadoop component (HDFS, Spark, Yarn, Map-Reduce, H base, HIVE, Impala) and related technologies. Technical Design and development of ETL/Hadoop and Analytics services /components Contribute in end to end architecture and process flow Understand Business requirement and publish reusable designs Result oriented approach with ability to provide apt solutions. Proficient in performance improvement & fine-tuning ETL and Hadoop implementations Conduct code reviews across projects. Takes responsibility for ensuring that build and code adhere to architectural and quality standards and policies. Can work independently with minimum supervision. Strong analytical and problem solving skills Experience/Exposure to SQL, advanced SQL skills Requirements Skills Set: Strong understanding of distributed computing architecture, core hadoop component (HDFS, Spark, Yarn, Map-Reuduce, H base, HIVE, Impala) and related technologies. Hands on experience with batch data ingestion (Sqoop) Expert level understanding of relational data structure and RDBMS as well as NoSQL databases (Cassandra, MongoDB, Elasticsearch) Experience with automation/Scheduling of workflows/jobs (via shell-scripting, Tivoli) Solid Grasp of data storage formats (Parquet, Avro, HBase, Cassandra) Understanding of Agile methodologies as well as SDLC life-cycles and processes. Strong Understanding of Data warehousing and lakes