{"id":3865131,"url":"https://alion.io/job/mach-senior-software-engineer","title":"Senior Software Engineer","company":{"id":2238233,"name":"MACH","domain":"mach.com","url":"https://alion.io/company/mach-com","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":null},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Apache NiFi","optional":false},{"name":"Cassandra","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Hadoop","optional":false},{"name":"HBase","optional":false},{"name":"Java","optional":false},{"name":"Linux","optional":false},{"name":"Machine Learning","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Unix","optional":false}],"status":"live","first_seen_at":"2026-11-06T11:43:51Z","employer_posted_date":"2026-11-06","last_verified_at":"2026-11-06T16:50:24Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Job Description\nJob Title\nSenior Data Engineer\nDepartment\nR&D\nPosition Type\nFull-time\nJob Location\nBangalore\nShift Timings\nRegular\nWork Mode\nHybrid\nIndustry Type\nTelecom\nTravel Required\nNA\nWhy Us?\nMACH is an innovator and leader in global monetization solutions. Their software optimizes and orchestrates critical inter-carrier business processes including data and financial clearing, network roaming, real-time campaign management, and interconnect solutions. MACH creates transformative communications solutions for today, tomorrow, and beyond, bridging wholesale and inter-carrier connectivity with roaming and clearing.\nCollaboration and Innovation are at MACH’s core. Our success is built on diverse strengths across different teams, functions, and geographies summarised in our company values:\nOpen collaboration\nDriving innovation\nCustomer commitment\nGrowth mindset\nDeliver results\nPlease visit our website to know more about us - https://mach.com/\nA Day in the Life of Senior Data Engineer:\nWe are seeking a highly skilled and analytical Senior Data Engineer with deep expertise in designing, building, and maintaining end-to-end distributed data pipelines within the Apache Hadoop ecosystem. In this role,\nYou will lead the architecture and implementation of scalable batch and real-time streaming pipelines.\nYou will be responsible for ingest, storage, large-scale processing, and serving layers, transforming massive volumes of unstructured, semi-structured, and structured data into high-performance datasets ready for downstream analytics and machine learning applications\nSo, how are we going to keep you busy?\n Pipeline Architecture: Design, build, and optimize scalable end-to-end data pipelines (ETL/ELT) using Hadoop ecosystem components.\nData Ingestion: Implement high-throughput ingestion pipelines utilizing Apache Nifi or Apache Kafka or Flume to capture streaming event data and transactional batch files.\nDistributed Processing: Develop robust data transformation workflows using Apache Spark (Core, SparkSQL, Structured Streaming) and MapReduce.\nData Storage & Modeling: Optimize data layout in HDFS utilizing columnar formats (Parquet, ORC) and manage NoSQL persistence layers using HBase or Cassandra\nQuery Performance Optimization: Author and tune highly complex distributed queries in Apache Hive to meet tight SLAs.\nOrchestration & Workflow Management: Automate and monitor multi-stage pipeline DAGs using orchestration tools like Apache Airflow or Oozie.\n Cluster Performance Tuning: Partner with DevOps/Infrastructure teams to debug issues related to data skew, resource allocation (YARN), cluster memory management, and Spark join strategies.\nWhat will make you eligible for this role?\nRelevant bachelor’s degree or master’s degree\n6-8 years of relevant experience in IT industry (Telecom preferred but not mandatory).\n3 to 7+ years of dedicated data engineering experience, with at least 3 years actively managing end-to-end production pipelines on Hadoop clusters\nProficiency working in Linux/Unix operating systems, shell scripting, and using code versioning tools like Git.\nExperience, that will be an advantage:\nCore Big Data Frameworks: Hands-on mastery of HDFS, MapReduce, YARN, Hive.\nDistributed Compute: Advanced proficiency in Apache Spark using Python (PySpark) or Scala.\n Streaming & Ingestion: Deep operational knowledge of Apache Nifi or Kafka (brokers, producers, consumers, and schema registry).\nProgramming Languages: Strong foundations in Python, SQL, and Scala or Java.\nNoSQL Database Systems: Direct experience handling unstructured/semi-structured data architectures in HBase, MongoDB, or Cassandra.\nData Warehouse & Modelling: Strong grasp of dimensional data modelling, star/snowflake schemas, and data governance practices.\nLimitation and Disclaimer:\nThe aforementioned job description is aimed to provide an overview of the overall type and level of work being performed for this role; it shouldn't be interpreted as a complete list of all obligations, responsibilities, and qualifications needed for the job.\nIn no way does this job description imply or say that these are the exclusive responsibilities of the employee holding this position. 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