Netscribes is a global leader in data, insights, and digital solutions, helping the worlds largest organizations accelerate growth and innovation. As a growth catalyst, we empower sales, marketing, product development, and strategy through a unique blend of domain expertise and technological capabilities. Our end-to-end solutions span data engineering, advanced analytics, AI, and intelligent automation - built to scale and adapt to dynamic business environments. We partner with clients across the implementation journey, aligning with their ecosystem to deliver actionable intelligence, operational efficiency, and competitive advantage.

LoB Overview :

Netscribes delivers integrated solutions across content, process, and technology to help global businesses scale efficiently and stay competitive in fast-moving markets. Our services are structured across three key areas :

Content Solutions :

We specialize in building, managing, and optimizing large-scale content ecosystems for global brands. Our expertise spans product data enrichment, taxonomy development, catalog and digital shelf management, content operations, and digital asset optimization. These solutions help improve product discoverability, streamline content workflows, and enhance customer experience across digital platforms.

Process Solutions :

Our research and insights-driven services support core business processes across marketing, product, customer experience, and operations. This includes market and competitive research, campaign analysis, customer intelligence, and content performance tracking. Through Information Management Services (IMS) and managed service models, we embed scalable, high-quality support directly into client workflows, ensuring agility, consistency, and speed.

Technology Solutions :

Complementing our content and process offerings, we bring advanced technology capabilities through data engineering, data analytics, and AI. From building unified data platforms and real-time dashboards to deploying intelligent automation and machine learning models, we help organizations modernize operations and unlock data-driven decisions at scale.

Profile Description :

Mandatory Skills :

- Snowflake : Data warehousing, performance tuning, clustering, data sharing, and Snowpipe

- Matillion : ETL/ELT pipeline design, orchestration, job scheduling, and transformation components

- SQL / Advanced SQL : Complex queries, stored procedures, window functions, query optimization

- Python / PySpark : Data processing, automation scripts, and distributed data transformation

- ETL/ELT Design : End-to-end pipeline architecture, incremental loads, SCD handling

- Data Modelling : Star/snowflake schema, dimensional modelling, data vault concepts

- Pipeline Orchestration : Scheduling, dependency management, error handling, and alerting

- Data Quality : Implementing validation checks, reconciliation, and data lineage tracking

Good to Have Skills :

- Cloud platforms : Azure Data Factory, Azure Synapse Analytics, or AWS Glue

- Apache Airflow or similar orchestration tools (Prefect, Dagster)

- dbt (Data Build Tool) for transformation layer management

- Delta Lake / Lakehouse architecture exposure

- Experience with BI tools : Power BI, Tableau, or Looker

- Version control : Git - branching strategies and CI/CD for data pipelines

- Certifications : Snowflake SnowPro Core, Matillion Associate, or equivalent

Key Responsibilities ETL / ELT Pipeline Development :

- Design, develop, and maintain scalable ETL/ELT pipelines using Matillion and Snowflake

- Build incremental and full-load data ingestion pipelines from diverse source systems (databases, APIs, flat files)

- Implement Slowly Changing Dimension (SCD) strategies and data merge patterns for accurate historical tracking

- Optimize Matillion jobs for performance, reusability, and maintainability

Snowflake Data Warehousing :

- Develop and manage Snowflake objects - databases, schemas, tables, views, streams, tasks, and pipes

- Tune query performance using clustering keys, materialized views, and warehouse sizing strategies

- Implement Snowpipe for real-time or near-real-time data ingestion requirements

- Manage Snowflake data sharing, role-based access controls, and governance policies

Data Transformation & Modelling :

- Write complex SQL transformations, stored procedures, and UDFs to support business logic

- Develop data models following star/snowflake schema and dimensional modelling best practices

- Build and maintain Python/PySpark scripts for large-scale data processing and automation

- Collaborate with data analysts and BI teams to ensure data models meet reporting requirements

Data Quality & Governance :

- Implement data quality checks, validation frameworks, and automated reconciliation processes

- Maintain data lineage documentation and pipeline metadata for governance and auditability

- Proactively monitor pipelines, set up alerting, and resolve failures or data anomalies

Collaboration & Delivery :

- Work closely with data architects, analysts, and business stakeholders to understand data requirements

- Write clean, modular, reusable, and well-documented code across SQL, Python, and Matillion

- Participate in code reviews and contribute to team best practices and documentation

- Provide regular updates on project status and proactively flag risks or blocker