{"id":1227368,"url":"https://alion.io/job/laksh-consultants-senior-data-engineer","title":"Senior Data Engineer","company":{"id":3800112,"name":"Laksh Consultants","domain":"lakshconsultants.com","url":"https://alion.io/company/laksh-consultants","size_band":null,"is_staffing_agency":true,"employer_type":"agency","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":"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":22000,"max_usd":44000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":51},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"CI/CD","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GitHub","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-09-24T11:45:37Z","employer_posted_date":null,"last_verified_at":"2026-09-24T11:45:37Z","board_verified":false,"closed_at":null,"days_open":5,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":5},"description":"Position : Senior Data Engineer (AWS)\n\nOverall/Total Experience : 4 - 8 years\n\nLocation : Bengaluru\n\nWorking Days : 5 Days from Office\n\nNotice Period Requirement : Immediate Joiners/Serving Notice Period Only\n\nClient's Company Size : Startup / Small Enterprise\n\nRoles & Responsibilities :\n\n- Create and maintain optimal data pipeline architecture for ETL/ELT into structured data.\n\n- Assemble large, complex data sets that meet business requirements and create multi-dimensional modelling like Star Schema and Snowflake Schema.\n\n- Expert level experience in creating scalable data warehouse including Fact tables, Dimensional tables and ingest datasets into cloud-based tools.\n\n- Identify, design, and implement internal process improvements including automating manual processes and optimising data delivery.\n\n- Collaborate with stakeholders to ensure seamless integration of data with internal data marts, enhancing advanced reporting.\n\n- Setup and maintain data ingestion, streaming, scheduling, and job monitoring automation using AWS services including Lambda, Code Pipeline, Glue, S3, and Redshift.\n\n- Build analytics tools that utilize the data pipeline to provide actionable insight into customer acquisition and operational efficiency.\n\n- Utilize GitHub for version control, code collaboration, and repository management.\n\nCandidate Requirements :\n\n- Must have at least 4+ years of hands-on data engineering experience with the recent 2+ years in AWS cloud data warehouses and AWS cloud services.\n\n- Must have advanced SQL knowledge and hands-on experience with relational databases and query authoring, plus a cloud data warehouse like AWS Redshift.\n\n- Must have expert-level experience creating scalable data warehouses - Fact tables, Dimensional tables, and ingesting datasets into cloud-based tools.\n\n- Must have strong multi-dimensional data modelling experience - Star Schema, Snowflake Schema, normalisation/de-normalisation, joins, OLAP cube modelling, and schema evolution while maintaining data integrity.\n\n- Must have hands-on experience creating and maintaining optimal ETL/ELT data pipeline architecture into structured data.\n\n- Must have experience setting up and maintaining data ingestion, streaming, scheduling, and job-monitoring automation using AWS services - Lambda, Glue, S3, Redshift, and Code Pipeline (CI/CD).\n\n- Must have experience building and optimizing big-data pipelines, architectures, and datasets, including data compression into PARQUET and SQL performance tuning.\nSkills\nAWS, SQL, ETL, Data Warehousing, Data Modeling, Data Engineering, Python, Snowflake DB, Data Pipeline","description_format":"text","description_chars":2617,"description_truncated":false,"requirements":{"experience_years_min":4,"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":[],"lifecycle":[{"event":"open","at":"2026-09-25T13:06:44Z"}],"liveness":{"score":54,"band":"ok","label":"Likely open","p_open":1,"p_active":0.542,"p_room":1,"age_days":4,"expected_fill_days":40,"reasons":["seen:4","agency","velocity","win:early"],"computed_at":"2026-09-29T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/laksh-consultants-senior-data-engineer","json_url":"https://alion.io/job/laksh-consultants-senior-data-engineer.json","meta":{"generated_at":"2026-09-30T02:23:10Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":1645,"day_limit":5000,"remaining_today":3355,"minute_limit":60,"resets_at":"2026-10-01T00:00:00Z"}}}