{"id":2602684,"url":"https://alion.io/job/norwin-technologies-data-engineer","title":"Data Engineer","company":{"id":3808915,"name":"Norwin Technologies","domain":"norwintechnologies.com","url":"https://alion.io/company/norwin-technologies","size_band":"11-50","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":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":16000,"max_usd":39000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":16},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Java","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"Amazon Kinesis","optional":true},{"name":"Amazon Redshift","optional":true},{"name":"Amazon S3","optional":true},{"name":"Databricks","optional":true},{"name":"DynamoDB","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-10-15T07:49:31Z","employer_posted_date":null,"last_verified_at":"2026-10-15T07:49:31Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"About the Role :\n\nWe are seeking a Data Engineer to build and optimise scalable data solutions for fraud detection, reporting and machine learning. This individual contributor role focuses on real-time streaming, large-scale data processing, cloud platforms and analytics engineering.\n\nKey Responsibilities :\n\n- Build and maintain scalable batch and real-time data pipelines for fraud analytics.\n\n- Develop and optimise Spark-based data processing frameworks.\n\n- Design Kafka-based streaming and event-driven architectures.\n\n- Implement efficient data ingestion frameworks and integrate multiple data sources.\n\n- Build and support Snowflake data warehouse and data lake solutions.\n\n- Develop data models for reporting, analytics, machine learning and fraud investigations.\n\n- Design scalable cloud data solutions using AWS and/or Azure.\n\n- Ensure data quality, governance, reliability, monitoring and compliance.\n\n- Collaborate with Data Scientists, Fraud Analysts and Engineering teams to deliver data-driven solutions.\n\n- Support production-grade analytics and ML platforms, ensuring reliability and performance.\n\nRequired Qualifications :\n\n- 4+ years of experience in Data Engineering or Big Data Engineering.\n\n- 2+ years of experience building large-scale distributed data processing systems.\n\n- Experience supporting production-grade analytics and machine learning platforms.\n\n- Strong hands-on experience with Apache Spark, Apache Kafka and Snowflake.\n\n- Experience developing scalable batch and streaming data pipelines.\n\n- Strong programming skills in Python, Scala or Java.\n\n- Experience working with AWS and/or Azure cloud data platforms.\n\nTech Stack :\n\n- Apache Spark: Large-scale distributed data processing, batch and streaming pipelines, performance tuning.\n\n- Apache Kafka: Event streaming, real-time data processing, messaging architectures.\n\n- Snowflake: Data warehousing, data modelling, ELT workflows, security.\n\n- Cloud: AWS (S3, Kinesis, DynamoDB, RDS, Glue, EMR, Redshift) or Azure (ADLS, ADF, Event Hubs, Synapse, Databricks, SQL).\n\n- Programming: Python, Scala or Java.\n\nPreferred Skills :\n\n- Experience in fraud analytics, fraud detection or transaction-related data processing.\n\n- Exposure to data lakes and modern data platform architectures.\n\n- Experience building and supporting ML data pipelines.\n\n- Knowledge of data governance, compliance and production monitoring.\n\nWork Location :\n\n- Bengaluru, Karnataka\n\nNotice Period :\n\n- Candidates who can join within 45 days are preferred.\n\nSkills\nData Engineering, Apache Spark, Python, AWS, Azure, Scala, Java, Kafka, Snowflake DB, Fraud Risk Implementation, ETL","description_format":"text","description_chars":2637,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Information Security","Cloud Consulting & 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