Data Engineer

About the job

About SoftSensor AI SoftSensor AI builds end-to-end enterprise data and AI solutions that help businesses make faster, better decisions. We design and deploy full-stack solutions spanning data engineering, analytics, Power BI dashboards, and decision support tools for clients across industries such as FMCG, manufacturing, BFSI, pharma, logistics, and retail. Data Engineering & Modeling Lead the design of end-to-end ELT/ETL pipelines to ingest, clean, transform, and enrich structured and semi-structured data from multiple source systems (ERP, CRM, web, apps, etc.). Define and implement canonical data models, conformed dimensions, and business-ready data marts on platforms such as Azure Fabric, Synapse, or Snowflake. Ensure data quality, lineage, governance, and performance through validation rules, reconciliation checks, logging, and alerting. Optimise query performance using appropriate partitioning, indexing, and modelling techniques. Document data contracts, assumptions, and SLAs clearly for downstream consumers. Business Intelligence & Reporting Design and own Power BI semantic models (star schemas, relationships, calculations, and row-level security). Enable self-serve analytics by documenting data models, measures, and usage patterns. Frame hypotheses and analytical approaches for problems such as revenue and margin analytics, supply chain and logistics cost drivers, customer behaviour and churn, and operational performance. Build and validate statistical and ML models (regression, classification, clustering, time-series forecasting) where appropriate. Summarise complex analyses into simple narratives and visuals for business reviews. Own scope, timelines, and risks for your workstream; You have designed and implemented a production-grade data mart (e.Sales & Margin, Supply Chain, or Customer 360) including ingestion, transformation, and documentation. A set of Power BI dashboards you own are in daily or weekly use by business leaders, with clear improvements in visibility and decision speed. You have led at least one advanced analytics initiative (for example, a demand forecast, churn model, or cost-driver analysis) and helped translate findings into real process or policy changes. A junior data scientist or analyst you mentor has significantly improved in code quality, problem structuring, or stakeholder handling, validated through feedback. Must-Have Skills & Experience ~5–10 years of experience delivering end-to-end data and analytics solutions in consulting or product environments. - Strong SQL and data-modelling skills (dimensional modelling, star/snowflake schemas). - Hands-on experience with at least one cloud data platform such as Azure Fabric, Synapse, Snowflake, BigQuery, or Redshift. - Solid experience with Power BI (or Tableau/Looker), including data models, calculations, and row-level security. - Proficiency in Python for data manipulation and analytics (pandas, numpy, basic scikit-learn or statsmodels). - Strong foundation in statistics and experimental design (confidence intervals, p-values, sample size, A/B tests). - Proven ability to translate business questions into data questions, and then into analyses and dashboards. - Experience with Azure Fabric end-to-end (Data Factory, Lakehouse, Warehouse, Power BI together). - Experience with dbt or similar transformation frameworks. - Industry experience in one or more of FMCG, manufacturing, BFSI, pharma, logistics, or retail. - Prior experience in client-facing consulting or working closely with global stakeholders. Fast growth and a clear path to Lead Data Scientist or Principal roles based on impact and ownership, not just tenure.

Requirements

• SQL
• Data Modeling
• Power BI
• Cloud Platforms
• Python

Preferred Technologies

• SQL
• Data Modeling
• Power BI
• Cloud Platforms
• Python

About the company

LMDmax Corp specializes in creating end-to-end data and AI solutions, enabling businesses to enhance their decision-making capabilities through advanced analytics.