{"id":2990375,"url":"https://alion.io/job/mathco-senior-data-engineer","title":"Senior Data Engineer","company":{"id":455909,"name":"MathCo","domain":"mathco.com","url":"https://alion.io/company/mathco","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","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":["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":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon EC2","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon EventBridge","optional":false},{"name":"Amazon Kinesis","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":"CI/CD","optional":false},{"name":"Data Vault","optional":false},{"name":"Databricks","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"DynamoDB","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"IAM","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scrum","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"CloudFormation","optional":true},{"name":"Docker","optional":true},{"name":"Kubernetes","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-21T09:44:03Z","employer_posted_date":"2026-10-21","last_verified_at":"2026-10-28T11:53:56Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"Job Description:\nThe Senior Data Engineer will be responsible for designing, developing, and maintaining scalable cloud-based data platforms and data pipelines. The role requires strong expertise in AWS, Snowflake, Databricks, Python, SQL, and PySpark, along with experience in batch and real-time data processing. The candidate will collaborate with cross-functional teams to build reliable, secure, and highperformance data solutions that support analytics, reporting, and AI/ML initiatives.\nKey Responsibilities:\nDesign, develop, and maintain scalable data pipelines and ETL/ELT frameworks.\nBuild and optimize batch and real-time streaming solutions using PySpark and cloud-native services. \nDevelop and manage enterprise data platforms using AWS, Snowflake, and Databricks. \nDesign and implement robust data models, data lakes, data warehouses, and lakehouse architectures. \nIntegrate data from multiple sources while ensuring data quality, governance, and security. \nOptimize performance and scalability of data processing workloads. \nCollaborate with Data Scientists, Analysts, Architects, and business stakeholders to deliver data solutions. \nImplement monitoring, alerting, and automated data validation processes\nContribute to architecture reviews, technical documentation, and best practices. \nMentor junior engineers and participate in code reviews. \nStay updated on emerging cloud and data engineering technologies. \nRequired Skills and Experience:\n5-8 years of relevant experience in Data Engineering, Big Data, and Cloud Data Platform development. \nStrong proficiency in Python, SQL, and PySpark. \nHands-on experience designing, developing, and maintaining scalable data platforms on AWS Cloud. \nStrong expertise in Snowflake and Databricks for enterprise-scale data engineering solutions. \nExperience building and optimizing batch and real-time streaming data pipelines.\nStrong understanding of Data Modeling concepts, including Dimensional \nModeling, Star Schema, Snowflake Schema, and Data Vault. \nExperience designing and implementing ETL/ELT pipelines for large-scale enterprise data platforms. \nStrong expertise in Apache Spark and distributed data processing frameworks.\nExperience building and managing Data Lakes, Data Warehouses, and Lakehouse architectures. \nHands-on experience with AWS services such as S3, Glue, EMR, Lambda, Redshift, Athena, EC2, ECS/EKS, Kinesis, MSK, Step Functions, CloudWatch, IAM, RDS, DynamoDB, EventBridge, SNS, and SQS. \nExperience integrating data from multiple structured and unstructured data sources. \nStrong understanding of data governance, security, data quality, and performance optimization best practices. \nExperience with version control systems such as Git and collaborative development workflows. \nProficiency with CI/CD pipelines and software engineering best practices. \nStrong problem-solving skills with the ability to debug, troubleshoot, and resolve complex data engineering challenges. \nAbility to design scalable and maintainable data solutions using modern architectural patterns and best practices. \nProven ability to work collaboratively in cross-functional teams, including participation in code reviews, technical discussions, and knowledge-sharing initiatives. \nExperience working in Agile/Scrum delivery environments. \nStrong communication skills and ability to interact with business and technical stakeholders. \nExperience in Healthcare, Pharma, or Real-World Evidence (RWE) data environments (good to have). \nExperience with Infrastructure as Code (Terraform/CloudFormation) (good to have). \nExperience with Docker and Kubernetes (good to have). \nKnowledge of Data Mesh, CDC, and Event-Driven Architectures (good to have). \nExposure to MLOps and AI/ML platform integration (good to have). \nAWS, Snowflake, or Databricks certifications (good to have).","description_format":"text","description_chars":3835,"description_truncated":false,"requirements":{"experience_years_min":5,"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":["Machine Learning","Analytics & BI 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