{"id":3215557,"url":"https://alion.io/job/unify-big-data-developer","title":"Big Data Developer","company":{"id":4471803,"name":"Unify","domain":"unifytech.com","url":"https://alion.io/company/unify-7","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":19500,"max_usd":42000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":75},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Apache Solr","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Cassandra","optional":false},{"name":"DynamoDB","optional":false},{"name":"ElasticSearch","optional":false},{"name":"Hadoop","optional":false},{"name":"Java","optional":false},{"name":"MLlib","optional":false},{"name":"MySQL","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-24T21:35:00Z","employer_posted_date":null,"last_verified_at":"2026-10-24T21:35:00Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"Responsibilities: \nCreate new and maintain existing Scala/Spark jobs for data transformation and aggregation from simple to complex data transformations involving structured and unstructured data.\nProduce unit tests for Spark transformations and helper performance optimisation methods.\nDevelop data processing pipelines, data storage, and management architecture.\nDefine scalable calculation logic for interactive and batch use cases\nInteract with infrastructure and data teams to produce complex analysis across data\nYou'll be working on a unique and challenging big data ecosystem with a focus on storage efficiency, data security and privacy, scalable and performant queries, expandability and flexibility, etc., and to help better measure the quality of map data.\nYou will work with engineers to build a big data platform that processes and manages exabytes of data and enables efficient access to that data.\n\nRequirements: \nMinimum 7 years of working experience in Big Data and Hadoop platforms, and building large-scale distributed systems with high availability.\nExperience in developing Spark Applications using Spark RDD API, Hadoop, Spark SQL, Spark Streaming API, Spark MLlib API, and DataFrames APIs\nShould have broad knowledge of Spark advantages, Spark workflows, how to write Spark jobs, Spark query tuning and performance optimisation.\nSolid in data structures and algorithm basics.\nShould have good hands-on experience with any one programming language (Scala/Java 8 - 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