{"id":3308987,"url":"https://alion.io/job/vsquare-systems-data-modeler","title":"Data Modeler","company":{"id":4431690,"name":"VSquare Systems","domain":"vsquaresystem.com","url":"https://alion.io/company/vsquare-systems","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":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, 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Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Oracle","optional":false},{"name":"PostgreSQL","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-27T01:59:14Z","employer_posted_date":null,"last_verified_at":"2026-10-27T01:59:14Z","board_verified":false,"closed_at":null,"days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"Job Title: Data Engineering + Data Modelling Lead\nExperience: 8 -10 Years\nLocation: Bangalore (Preferred) / Remote\nJob Responsibilities: \nLead end-to-end data engineering and data modeling initiatives, including requirements gathering, solution design, development, testing, deployment, andoperational support.\nDevelop scalable, high-performance data pipelines using PySpark and Apache Spark for data ingestion, transformation, integration, and loading acrossenterprise platforms.\nDefine and implement enterprise-wide conceptual, logical, and physical data models to support business, analytical, and operational requirements.\nDesign and maintain database schemas, tables, views, indexes, and data structures that support both transactional and analytical workloads.\nLead the development of ETL/ELT frameworks and reusable components to ensure efficient and standardized data processing.\nImplement data quality frameworks, validation rules, profiling techniques, and monitoring processes to ensure data accuracy, completeness, consistency, andreliability.\nOptimize data models, ETL pipelines, database performance, and Spark workloads to improve scalability, processing efficiency, and query performance.\nDocument data models, data lineage, ETL workflows, metadata, and technical designs in a clear and comprehensive manner.\nProvide technical leadership and mentorship to development teams.\nRequired Experience & Skills:\n6-8 years of experience in Data Engineering, ETL/ELT Development, and Data Modeling, with demonstrated experience leading enterprise-scale data initiatives and deliveryteams.\nStrong expertise in Databricks/Snowflake(or similar ETL tools), PySpark, Apache Spark, Spark SQL, and Python for designing, developing, and optimizing high-volume datapipelines and distributed data processing solutions.\nProven experience in designing Conceptual, Logical, and Physical Data Models, including ER Modeling, Dimensional Modeling, Data Vault, and normalization/denormalizationtechniques.\nHands-on experience with data lake, data warehouse, and cloud-based data platforms such as Databricks, Snowflake, AWS, or Azure.\nStrong knowledge of relational databases and performance tuning, including Oracle, SQL Server, PostgreSQL, Snowflake, schema design, indexing, and query optimization.\nExperience with data integration and orchestration technologies such as Apache Airflow, Kafka, NiFi, or equivalent enterprise data movement tools.\nSolid understanding of data governance, metadata management, data lineage, and data quality frameworks, with the ability to establish enterprise data standards and bestpractices.\nJob Title: Data Engineering + Data Modelling Lead\nExperience: 6–8 Years\nLocation: Bangalore (Preferred) / Remote\nJob Responsibilities: \nLead end-to-end data engineering and data modeling initiatives, including requirements gathering, solution design, development, testing, deployment, andoperational support.\nDevelop scalable, high-performance data pipelines using PySpark and Apache Spark for data ingestion, transformation, integration, and loading acrossenterprise platforms.\nDefine and implement enterprise-wide conceptual, logical, and physical data models to support business, analytical, and operational requirements.\nDesign and maintain database schemas, tables, views, indexes, and data structures that support both transactional and analytical workloads.\nLead the development of ETL/ELT frameworks and reusable components to ensure efficient and standardized data processing.\nImplement data quality frameworks, validation rules, profiling techniques, and monitoring processes to ensure data accuracy, completeness, consistency, andreliability.\nOptimize data models, ETL pipelines, database performance, and Spark workloads to improve scalability, processing efficiency, and query performance.\nDocument data models, data lineage, ETL workflows, metadata, and technical designs in a clear and comprehensive manner.\nProvide technical leadership and mentorship to development teams.\nRequired Experience & Skills:\n6-8 years of experience in Data Engineering, ETL/ELT Development, and Data Modeling, with demonstrated experience leading enterprise-scale data initiatives and deliveryteams.\nStrong expertise in Databricks/Snowflake(or similar ETL tools), PySpark, Apache Spark, Spark SQL, and Python for designing, developing, and optimizing high-volume datapipelines and distributed data processing solutions.\nProven experience in designing Conceptual, Logical, and Physical Data Models, including ER Modeling, Dimensional Modeling, Data Vault, and normalization/denormalizationtechniques.\nHands-on experience with data lake, data warehouse, and cloud-based data platforms such as Databricks, Snowflake, AWS, or Azure.\nStrong knowledge of relational databases and performance tuning, including Oracle, SQL Server, PostgreSQL, Snowflake, schema design, indexing, and query optimization.\nExperience with data integration and orchestration technologies such as Apache Airflow, Kafka, NiFi, or equivalent enterprise data movement tools.\nSolid understanding of data governance, metadata management, data lineage, and data quality frameworks, with the ability to establish enterprise data standards and 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