{"id":2381988,"url":"https://alion.io/job/dynatronsoftware-data-engineer-remote-india-dynatron","title":"Data Engineer - Remote India - Dynatron","company":{"id":4418891,"name":"Dynatron Software","domain":"dynatronsoftware.com","url":"https://alion.io/company/dynatronsoftware","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"JazzHR","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":{"label":"UTC-8 – UTC-5","utc_offset_min":-8,"utc_offset_max":-5},"hiring_geo_confidence":"explicit","locations":[],"countries":[],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":{"min":5750000,"max":null,"currency":"INR","period":"year","gross":null,"usd_annual":60214},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Amazon Kinesis","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Glue","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"Cortex","optional":false},{"name":"Databricks","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Feature Store","optional":false},{"name":"Fivetran","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Prometheus","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-12T19:34:13Z","employer_posted_date":"2026-10-12","last_verified_at":"2026-10-12T19:34:13Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About Dynatron\nDynatron is championing a new standard of Fixed Ops excellence for automotive dealerships. We cut through the Fixed Ops data fog and deliver unique insights and actions that help you drive revenue growth, expand margins, and uplift retention-all through a unique AI-powered Fixed Ops Data Intelligence Platform, proven methodology, and expert coaching.\nThe Opportunity\nDynatron is seeking a highly skilled India based - remote Data Engineer to join our growing data team. While our architects define the blueprint, you will be the lead craftsman responsible for building, optimizing, and maintaining the robust data pipelines that power our real-time analytics, AI/ML initiatives, and enterprise reporting. You are a hands-on expert in AWS and modern cloud data stacks, specifically Snowflake or Databricks, and possess the\nengineering rigor to build scalable, production-grade data ecosystems.\nHours of Expectation\nCritical hours to be available for collaboration with the US team are:\n9:00 AM - 2:00 PM EST\n8:00 AM - 1:00 PM CST\n7:00 AM - 12:00 PM MST\n6:00 AM - 11:00 AM PST\nThe balance of 3 hours each day can be worked before or after core hours at your discretion.\nThis role includes on-call responsibilities; the engineer is expected to participate in a rotation to monitor pipeline health and respond to production data issues outside of core hours as needed.\nWhat You’ll Do Pipeline Development & AWS Data Lake Engineering\nBuild and maintain complex data pipelines using AWS Glue, Step Functions, or Databricks Workflows. \nImplement modular data structures using advanced modeling techniques such as Medallion Architecture and Dimensional Modeling. \nManage scalable data storage solutions using AWS S3 as the primary landing zone and data lake foundation. \nOptimize storage formats (Delta, Iceberg, Parquet) and compute performance to ensure high-throughput and cost-effective processing. \nBuild decoupled, event-driven architectures using AWS SNS and SQS to handle high-throughput messaging between data services. \n Real-Time Data Streaming & IngestionDevelop and deploy real-time ingestion pipelines using AWS Kinesis or Kafka. \nImplement Change Data Capture (CDC) via tools like Debezium or Fivetran to support low-latency operational analytics. \n Core Data Quality & Automated Validation (QA Ownership)Own end-to-end data validation and QA by building automated data quality checks directly into the ETL/ELT pipelines.\nEnforce strict data contracts and schema evolution guidelines to maintain high data quality and integrity across domains. \nImplement proactive alerting and observability to catch data drift, pipeline anomalies, and quality drops before they impact downstream users. \nEngineering for ML/AIEngineer ML-ready datasets and manage Feature Stores to support the Data Science team. \nOperationalize ML workflows, integrating with services like Snowflake Cortex, Databricks AI, or AWS Bedrock. \nTechnical Leadership & CollaborationAdhere to coding best practices, SQL optimization, and Python development. \nCollaborate closely with Product and ML teams to translate architectural designs into functional code. \n Required QualificationsExperience: 5+ years of experience in data engineering with a focus on large-scale distributed systems. \nCore Languages: Expert-level Python and PySpark with Strong SQL skills.\nPlatforms: Deep hands-on experience with Snowflake or Databricks, built natively within an AWS ecosystem. \nStreaming: Proven track record building streaming applications using Kinesis or Kafka. \nData Validation: Demonstrated experience implementing automated testing frameworks, data profiling, and pipeline validation (owning the QA of your own pipelines).\nSoft Skills: Strong documentation habits (playbooks, technical specs) and an ownership mindset. \nCertifications (Nice-to-Have): Relevant IT professional certifications, such as SnowPro Core, Databricks Certified Data Engineer Professional, or AWS Certified Data Engineer. \nCollaboration & Ownership\nStrong communication skills with the ability to explain technical concepts clearly to technical and non-technical stakeholders.\nCollaborative mindset with the ability to partner effectively across Product, Engineering, Analytics, ML, and leadership teams.\nHigh standards for quality, maintainability, performance, and operational discipline.\nStrong ownership mindset with the ability to move quickly, solve problems thoughtfully, \nWhat Success Looks Like\nThis role rewards data engineers who:\nBuild scalable, reliable, and secure data systems that support real business outcomes.\nOperate with urgency, ownership, and strong engineering discipline.\nThink beyond individual pipelines to improve platform quality, observability, and long-term maintainability.\nHelp Dynatron turn trusted data into smarter products, better decisions, and stronger customer outcomes and follow through reliably.\nPartner effectively across technical and business teams.\nCompensation & Benefits\n Competitive base salary: $5,750,000 INR/yr\nParticipation in Dynatron’s Equity Incentive Plan\nComprehensive health, dental, and vision insurance\nEmployer-paid disability and life insurance\n401(k) with competitive company match\nFlexible vacation policy and 11 paid holidays\nRemote-first culture\nOngoing professional development opportunities","description_format":"text","description_chars":5317,"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":["Equity","Flexible vacation policy","Life insurance","Professional 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