{"id":3321617,"url":"https://alion.io/job/fractal-data-engineer-3","title":"Data Engineer","company":{"id":3877848,"name":"Fractal","domain":"fractal.com","url":"https://alion.io/company/fractal-com","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":"full_time","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":21000,"max_usd":46000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":75},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"pySpark","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Agile","optional":true},{"name":"Platform Engineering","optional":true},{"name":"Python","optional":true}],"status":"live","first_seen_at":"2026-10-27T00:38:59Z","employer_posted_date":null,"last_verified_at":"2026-10-27T00:38:59Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"Job Profile - AWS Senior Data Engineer\nExperience Required – 6-8 yrs\nJob Location – All Fractal locations.\nNote - Immediate to 30 days preferred.\n\nkindly share your resume at - [HIDDEN TEXT]\n\nJob Description\nRole Summary\nWe are looking for a highly motivated Data Engineer with 6 years of hands-on experience in AWS Databricks to join our data platform team. The role involves working closely with data scientists, analysts, architects, and business stakeholders to design, build, and maintain scalable, high-performance data pipelines and data solutions within the AWS cloud environment.\nThe ideal candidate should have strong expertise in Databricks, PySpark, SQL, Delta Lake, and AWS data services, along with a good understanding of modern data engineering practices, orchestration, and data governance.\nKey Responsibilities\nDesign, develop, test, and deploy scalable ETL/ELT pipelines using AWS Databricks, PySpark, and SQL.\nBuild and maintain robust data pipelines for ingesting and processing structured and unstructured data from multiple sources such as Amazon S3, Amazon RDS, APIs, and external platforms.\nImplement and manage Delta Lake solutions to support both batch and streaming data processing.\nOptimize Spark workloads for performance, scalability, and cost efficiency.\nEnsure data quality, consistency, reliability, and integrity through validations, monitoring, exception handling, and reconciliation checks.\nCollaborate with cross-functional teams including data analysts, data modelers, architects, and business stakeholders to support reporting, analytics, and downstream consumption.\nSupport orchestration and scheduling of pipelines using tools such as AWS Glue Workflows, Apache Airflow, or AWS Step Functions.\nParticipate in CI/CD implementation and code deployment processes using Git, AWS CodePipeline, and CodeBuild.\nApply best practices related to data governance, metadata management, security, and access control.\nSupport production issue resolution, ad hoc data requests, and continuous improvement of the data platform.\nRequired Skills and Qualifications\nBachelor's degree in computer science, Information Systems, Engineering, or a related discipline.\n5 years of experience in Data Engineering or a similar role.\nStrong hands-on experience with AWS Databricks.\nGood proficiency in PySpark and SQL for large-scale data processing.\nExperience working with Delta Lake and modern lakehouse concepts.\nFamiliarity with AWS services such as Amazon S3, Amazon RDS, AWS Glue, AWS Lambda, and Amazon Redshift.\nKnowledge of batch and streaming data architectures.\nExperience with workflow orchestration, monitoring, and debugging of pipelines.\nUnderstanding of version control and CI/CD practices.\nAwareness of data security, governance, and metadata management principles.\nStrong analytical, problem-solving, and communication skills.\nPreferred Qualifications\nExperience in building data pipelines in enterprise-scale cloud data platforms.\nFamiliarity with real-time / streaming frameworks and event-driven architectures.\nExposure to data quality frameworks, reconciliation processes, and operational monitoring.\nWorking knowledge of infrastructure automation and cloud deployment best practices.\nExperience collaborating in agile delivery environments.\nKey Competencies\nStrong problem-solving orientation\nAttention to detail and focus on data quality\nAbility to work in a fast-paced, collaborative environment\nGood stakeholder communication and coordination skills\nOwnership mindset with a focus on delivery excellence\nNice to Have\nExperience with data modeling and analytics enablement\nExposure to DevOps and platform engineering practices\nCertification in AWS or Databricks technologies\nWhy Join Us\nThis role offers the opportunity to work at the forefront of cloud-based data engineering, partnering with talented data scientists, analysts, and architects to build scalable, high-impact data solutions on AWS 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