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Requirements and responsibilities
This role profiles and refactors existing data pipelines, builds and optimizes new ingestion, transformation, and orchestration workflows, and implements data models and frameworks that align with the agreed target state. This role collaborate with the Client Data Engineering team to turn the prioritized backlog into actionable technical tasks, establish engineering best practices (CI/CD, testing, observability, performance tuning), and ensure production-grade, reliable data assets that support analytics and downstream applications.Key ResponsibilitiesImplement and enhance end‑to‑end data pipelines (batch and/or streaming) to ingest data from diverse source systems into the enterprise data platform, following agreed architecture and patterns.Engineer robust ETL/ELT workflows to transform, cleanse, and standardize data, ensuring conformance with canonical data models and business rules.Build and optimize data layers (raw, curated, semantic) that enable self‑service analytics, BI, and data‑science use cases, with particular focus on performance, scalability, and cost efficiency.Industrialize data solutions by implementing re‑usable frameworks, templates, and components for ingestion, quality checks, logging, and monitoring.Contribute to data modeling activities (conceptual, logical, physical) and translate models into physical structures in the target data platform/warehouse.Tune queries, jobs, and storage layouts to meet SLAs for latency, throughput, and concurrency, leveraging partitioning, indexing, caching, and other optimization techniques supported by the platform.Implement and adhere to security, privacy, and governance standards, including role‑based access controls, data masking, and lineage/metadata capture.Required Skills & Experience5+ years in data engineering, analytics engineering, or data platform rolesDeep expertise in Google BigQuery — data modeling, optimization, and governanceExperience with Python ETL and SQL pipelinesFamiliarity with BI tools in the modern data stack (Periscope, Looker, Metabase, Tableau, or equivalents)Strong understanding of data governance — lineage, cataloging, PII controls, and access managementExcellent stakeholder engagement and discovery facilitation skillsNice to HaveBasic experience/knowledge in dbt (data build tool) — project setup, testing, and documentationExperience with Amplitude or other product analytics platformsPrior work in EdTech or B2C SaaS data environmentsExposure to AI for BI or semantic layer tooWe offer friend of friend Incentive. Kindly refer & get benefited with Incentive. Interested candidates or referrals kindly send updated resume to Bharat.raju@nexturn.com.
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