{"id":2803695,"url":"https://alion.io/job/nexifyr-consulting-data-engineer","title":"Data Engineer","company":{"id":3809932,"name":"Nexifyr Consulting","domain":"nexifyr.in","url":"https://alion.io/company/nexifyr-consulting-private-limited","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":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":46000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":59},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon EC2","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"Boto3","optional":false},{"name":"CI/CD","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"Git","optional":false},{"name":"IAM","optional":false},{"name":"Power BI","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":"Azure","optional":true},{"name":"Databricks","optional":true},{"name":"ETL/ELT","optional":true},{"name":"Talend","optional":true}],"status":"closed","first_seen_at":"2026-07-21T04:48:19Z","employer_posted_date":null,"last_verified_at":"2026-10-19T04:49:04Z","board_verified":false,"closed_at":"2026-10-19T04:49:04Z","days_open":90,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":90},"description":"Role : Data Engineer (Snowflake / DBT / Python / PySpark)\n\nExperience : 6+ years in data engineering / cloud data warehousing\n\nLocation : Bangalore, India (Hybrid / Onsite as required)\n\nEmployment Type : Full-time\n\nNotice Period : Immediate to 30 days preferred\n\nAbout the Role : \n\nWe are looking for a hands-on Data Engineer with strong expertise in Snowflake, DBT, Python, and PySpark to design, build, and optimize scalable ELT data pipelines and cloud-based analytics platforms. You will work with enterprise clients across domains such as healthcare, manufacturing, and retail, delivering high-performance data integration, transformation, and analytics solutions on AWS.\n\nAbout organisation : \n\nWe are an Indian IT services and consulting firm based in Bengaluru. Founded in 2024, the company delivers digital transformation solutions to global B2B clients.\n\nCore Capabilities : \n\n- Artificial Intelligence : Building AI/ML models and automated chatbots.\n\n- Data & Cloud : Managing data engineering and cloud migrations.\n\n- Automation : Implementing Robotic Process Automation (RPA) workflows.\n\n- Core Focus : Specialises in AI/ML solutions, cloud platforms, data engineering, and automation.\n\n- Target Market : Modernises operations primarily for business-to-business (B2B) clients globally.\n\n- Footprint : Operates from India but serves customers across the US and UAE.\n\nKey Responsibilities : \n\n- Design and implement end-to-end ELT data pipelines using Snowflake and DBT for enterprise analytics workloads.\n\n- Develop modular, well-tested DBT models (staging, intermediate, marts) with incremental loading strategies, snapshots, and SCD Type-2 logic for historical dimensions.\n\n- Build and maintain large-scale distributed data processing jobs using PySpark for batch and near real-time transformation workloads.\n\n- Write production-grade Python code for data validation, reconciliation, automation, and orchestration of pipeline workflows.\n\n- Automate cloud data ingestion using AWS S3, Snowpipe, Streams and Tasks for incremental and near real-time processing.\n\n- Design fact and dimension tables following star and snowflake schema architecture for enterprise reporting.\n\n- Optimize Snowflake query performance and warehouse utilization to reduce compute cost - clustering, pruning, caching, and SQL tuning.\n\n- Implement CI/CD and version control practices (Git) for DBT projects and data pipeline code.\n\n- Ensure data quality, testing, and documentation across all pipeline layers (DBT tests, custom validation frameworks).\n\n- Collaborate with BI/analytics teams (Power BI) to deliver analytics-ready datasets and support data validation for dashboards.\n\nMust-Have Skills : \n\n- DBT : Strong hands-on experience building transformation workflows - models, macros, Jinja templating, incremental models, tests, snapshots, and documentation.\n\n- Python : Advanced scripting for data processing, automation, API integration, and validation frameworks (pandas, boto3, etc.).\n\n- PySpark : Experience developing and tuning Spark jobs - DataFrames, partitioning, joins, window functions, and performance optimization on large datasets.\n\n- Snowflake : Deep knowledge of architecture, virtual warehouses, Snowpipe, Streams & Tasks, Time Travel, zero-copy cloning, and performance tuning.\n\n- SQL : Expert-level query writing, optimization, and data modeling (star/snowflake schemas, SCD handling).\n\n- AWS : Working experience with S3, IAM, EC2, and event-driven ingestion patterns.\n\nGood-to-Have Skills : \n\n- Experience with ETL tools such as Talend, Airflow, or similar orchestration frameworks.\n\n- Exposure to Databricks, EMR, or Glue for Spark workloads.\n\n- Familiarity with Power BI or other visualization tools for data validation and QA support.\n\n- Snowflake SnowPro Core certification (or equivalent).\n\n- Experience in healthcare, pharma, manufacturing, or supply-chain analytics domains.\n\nQualifications : \n\n- Bachelor's degree in Engineering, Computer Science, or a related field (B.Tech / B.E. / MCA).\n\n- 6+ years of professional experience in data engineering, with at least 2 years on Snowflake and DBT.\n\nWhat We Look For : \n\n- Strong analytical and problem-solving skills with a focus on data quality and reliability.\n\n- Ability to work independently, own deliverables end-to-end, and communicate clearly with client stakeholders.\n\n- Quick learner of modern cloud and data engineering technologies\nSkills\nData Engineering, Snowflake DB, Data Build Tool, Python, PySpark, ETL, Data Pipeline, Data Integration, Data Analytics, Apache Airflow, Azure 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