Bigdata Engineer -Spark
Marktine Technology Solutions Pvt Ltd
If you want to work with data at scale from day one, this Big Data Engineer role gives you real hands-on experience with distributed systems. You'll own projects that process massive datasets and build the infrastructure others rely on. It's the kind of work that teaches you how modern data systems actually work.
Your responsibilities include designing and building ETL pipelines using Spark, Hadoop, and related tools like HDFS and Hive. You'll translate business requirements into reusable system designs, improve performance across data platforms, and conduct code reviews to maintain quality standards. The work is independent—you'll own pieces end-to-end.
This fits you if you have hands-on experience with Hadoop components, strong SQL skills, and understand distributed computing concepts. A computer science or engineering background helps, as does any portfolio work with batch processing or data systems. You should be comfortable working solo and solving complex technical problems.
Ready to apply. Head to CareerJumpShip, search this posting, and submit your resume and portfolio. Include a note about your biggest data or systems project so far.
About this role
Category: Technology Location: 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 Details Originally posted on Himalayas
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