{"id":2902517,"url":"https://alion.io/job/systango-technologies-limited-data-engineer-etlsnowflake-s04","title":"Data Engineer-ETL/Snowflake (S04)","company":{"id":450069,"name":"Systango Technologies Limited","domain":"systango.com","url":"https://alion.io/company/systango-technologies-limited","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Keka","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":["Indore, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":19000,"max_usd":41000,"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":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Airflow","optional":true},{"name":"Apache Kafka","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"CI/CD","optional":true},{"name":"dbt","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"Kubernetes","optional":true},{"name":"Machine Learning","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-09-21T09:55:03Z","employer_posted_date":"2026-09-21","last_verified_at":"2026-10-29T17:02:58Z","board_verified":true,"closed_at":null,"days_open":38,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":38},"description":"About US:\nSystango Technologies Limited (NSE: SYSTANGO) is a digital engineering company that offers enterprise-class IT and product engineering services to different size organizations. At Systango, we have a culture of efficiency - we use the best-in-breed technologies to commit quality at speed and world-class support to address critical business challenges. We leverage Gen AI, AI/Machine Learning and Blockchain to unlock the next stage of digitalization for traditional businesses. Our handpicked team is adept at web & enterprise development, mobile apps, QA and DevOps. Sila, Cuentas, Youtility, Porsche, MGM Grand, Deloitte, Grindr, and Tawk.to are some of the top clients that have entrusted us to enhance their digital capabilities and build disruptive innovations. We believe in making the impossible, Possible and we do it literally.\nWe are looking for an experienced Data Engineer with 8+ years of hands-on experience in designing, developing, and maintaining scalable data engineering solutions.\nThe ideal candidate should have a strong Python and Data Engineering background, with hands-on expertise in Snowflake, ETL/ELT pipelines, Databricks/PySpark, Medallion Architecture, and data quality validation.\nThe role requires someone who can independently understand requirements, design data solutions, build production-grade pipelines, and take ownership of delivery end-to-end.\nKey Responsibilities\nDesign, develop, and maintain robust ETL/ELT data pipelines for large-scale data processing.\nDevelop production-grade data engineering solutions using Python, SQL, Snowflake, and Databricks/PySpark.\nWork with Medallion Architecture (Bronze, Silver, Gold layers) for building scalable and reliable data platforms.\nDesign and implement data transformation, cleansing, validation, and enrichment processes.\nImplement Data Completeness, Data Consistency, Data Deduplication, and Data Quality (DCDQ) checks across data pipelines.\nEnsure data accuracy, reliability, consistency, and availability across different stages of the data pipeline.\nWork with Snowflake for data storage, transformation, optimization, and performance tuning.\nBuild and optimize data processing pipelines using Databricks and PySpark.\nDevelop complex SQL queries and perform data modelling for analytical workloads.\nIntegrate data from multiple sources and build scalable data pipelines.\nTroubleshoot pipeline failures, data-quality issues, and performance bottlenecks.\nCollaborate with product, engineering, and business stakeholders to understand requirements and translate them into effective data solutions.\nIndependently drive projects from requirement gathering → solution design → development → testing → deployment → production support.\nFollow engineering best practices around code quality, testing, monitoring, documentation, and maintainability.\nRequired Skills\nData Engineering\n8+ years of strong hands-on experience in Data Engineering.\nStrong experience designing and developing production-grade ETL/ELT pipelines.\nStrong understanding of data pipelines, data warehousing, data modelling, and data transformation.\nExperience working with Medallion Architecture - Bronze, Silver, and Gold layers.\nStrong understanding of data quality, validation, reconciliation, and DCDQ checks.\nProgramming\nStrong hands-on Python programming experience.\nAdvanced SQL skills.\nHands-on experience with Apache Spark / PySpark.\nAbility to write clean, reusable, maintainable production code.\nData Platforms\nStrong hands-on experience with Snowflake.\nExperience with Databricks and PySpark.\nGood understanding of modern data warehouse/lakehouse concepts.\nExperience with Delta Lake or similar technologies is a plus.\nData Processing & Orchestration\nExperience building and managing batch data pipelines.\nExperience with data pipeline orchestration tools such as Airflow, Databricks Workflows, or similar.\nExperience with streaming technologies such as Kafka is a plus.\nData Quality\nStrong understanding of data quality frameworks and validation mechanisms.\nExperience implementing checks for:Data completeness\nData consistency\nData duplication\nData accuracy\nData reconciliation\n\nAbility to identify and troubleshoot data-quality issues across different pipeline stages.\nCloud & Other Technologies\nExposure to AWS, Azure, or GCP is good to have but not mandatory.\nExperience with CI/CD, Docker, Terraform, or Kubernetes is a plus.\nExperience with dbt is a plus.\nWhat We Are Looking For\nStrong Python-first Data Engineering background.\n8+ years of relevant experience with significant hands-on development.\nStrong Snowflake + ETL/ELT experience.\nGood hands-on experience with Databricks/PySpark.\nPractical understanding of Medallion Architecture.\nStrong focus on data quality and DCDQ checks.\nAbility to independently own data engineering projects from requirements through production.\nStrong problem-solving and analytical skills.\nGood communication and stakeholder-management skills.\nAbility to understand business requirements, ask the right questions, and convert them into scalable technical solutions.","description_format":"text","description_chars":5084,"description_truncated":false,"requirements":{"experience_years_min":8,"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":["LLM & Generative 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