{"id":3318325,"url":"https://alion.io/job/unisys-senior-data-engineer","title":"Senior Data Engineer","company":{"id":6839,"name":"Unisys","domain":"unisys.com","url":"https://alion.io/company/unisys","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":78,"open_postings":76,"ghost_share":0,"stale_share":0.868,"repost_share":0,"time_to_fill_p50_days":28,"computed_at":"2026-10-30T05:48:23Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","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":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon EventBridge","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"DynamoDB","optional":false},{"name":"ElasticSearch","optional":false},{"name":"ETL/ELT","optional":false},{"name":"IAM","optional":false},{"name":"Java","optional":false},{"name":"OpenSearch","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Agile","optional":true},{"name":"Airflow","optional":true},{"name":"Amazon Kinesis","optional":true},{"name":"Apache Kafka","optional":true},{"name":"CI/CD","optional":true},{"name":"Databricks","optional":true},{"name":"Delta Lake","optional":true},{"name":"Docker","optional":true},{"name":"Kubernetes","optional":true},{"name":"Machine Learning","optional":true},{"name":"Scrum","optional":true},{"name":"Snowflake","optional":true},{"name":"Spark","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-26T00:00:00Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-10-30T20:21:09Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"What success looks like in this role:\nWe are seeking an experienced Senior Data Engineer to design, build, and maintain scalable data platforms and data processing pipelines. The ideal candidate will have strong expertise in Python, PySpark, AWS, DynamoDB, and OpenSearch, along with exposure to Java. This role requires hands-on experience building cloud-native big data solutions, optimizing large-scale data processing workloads, and enabling data-driven decision-making across the organization.\nKey Responsibilities\nDesign, develop, and maintain large-scale data pipelines using Python and PySpark.\nBuild and optimize batch and near real-time data processing solutions.\nDesign scalable data architectures on AWS.\nDevelop ETL/ELT workflows for ingesting, transforming, and publishing datasets.\nWork with structured and semi-structured data from multiple sources.\nDesign and maintain NoSQL database solutions using DynamoDB.\nImplement search and analytics solutions using OpenSearch.\nOptimize data processing jobs for performance, scalability, and cost efficiency.\nCollaborate with product teams, architects, and software engineers to define data requirements.\nMonitor, troubleshoot, and resolve data platform and pipeline issues.\nImplement data quality, governance, security, and observability best practices.\nParticipate in code reviews and mentor junior engineers.\nRequired Technical Skills\nData Engineering\nStrong expertise in Python.\nExtensive experience with PySpark and distributed data processing.\nHands-on experience building data lakes and modern data platforms.\nStrong understanding of ETL/ELT frameworks and data modeling.\nExperience processing large datasets efficiently.\nAWS Cloud\nExpert-level knowledge of AWS services such as:\nEMR\nGlue\nLambda\nS3\nAthena\nRedshift\nECS/EKS\nStep Functions\nEventBridge\nIAM\nCloudWatch\nSNS/SQS\nDatabases\nStrong SQL skills and query optimization experience.\nExperience with NoSQL databases, particularly DynamoDB.\nUnderstanding of partitioning, indexing, and data access patterns.\nSearch & Analytics\nHands-on experience with OpenSearch / Elasticsearch.\nExperience designing indexes and search schemas.\nKnowledge of query optimization and search performance tuning.\nExperience implementing analytics and monitoring dashboards.\nProgramming\nStrong Python development skills.\nWorking knowledge of Java.\nUnderstanding of object-oriented programming and software engineering best practices.\nPreferred Qualifications\nBachelor's or Master's degree in Computer Science, Engineering, or a related field.\n8+ years of experience in Data Engineering.\nExperience with streaming platforms such as Kafka or Kinesis.\nExperience with Airflow or other workflow orchestration tools.\nExperience with Docker and Kubernetes.\nExposure to Data Lake and Lakehouse architecture.\nExperience in Agile/Scrum development environments.\nGood to Have\nApache Kafka\nApache Airflow\nTerraform\nDatabricks\nDelta Lake\nSnowflake\nCI/CD pipelines\nMachine Learning data pipelines\nKey Competencies\nStrong problem-solving and analytical skills.\nAbility to work in a fast-paced, cloud-native environment.\nExcellent communication and stakeholder management skills.\nStrong ownership and accountability mindset.\nAbility to mentor and guide team members.\nYou will be successful in this role if you have:\nBA/BS degree and 8-10 years’ relevant experience OR equivalent combination of education and experience\nUnisys is proud to be an equal opportunity employer that considers all qualified applicants without regard to age, blood type, caste, citizenship, color, disability, family medical history, family status, ethnicity, gender, gender expression, gender identity, genetic information, marital status, national origin, parental status, pregnancy, race, religion, sex, sexual orientation, transgender status, veteran status or any other category protected by law.\nLocal employment practices and rights may vary by jurisdiction and are subject to applicable local laws. This commitment includes our efforts to provide for all those who seek to express interest in employment the opportunity to participate without barriers.\nIf you are a US job seeker unable to review the job opportunities herein, or cannot otherwise complete your expression of interest, without additional assistance and would like to discuss a request for reasonable accommodation, please contact our Global Recruiting organization at . 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