You will serve as the bridge between raw data sources and actionable analytics, working closely with cross-functional partners in analytics, product, and engineering.

Your focus will be on delivering clean, welltested, and performant data models that power businesscritical dashboards, machine learning workflows, and datadriven decisionmaking across the organization.

Requirements :

Education : Bachelor's or Master's degree in Computer Science, Software Engineering, Information Systems, Mathematics, or a related technical discipline (or equivalent practical experience).

Technical Proficiency :

- Demonstrated proficiency in writing modular, PEP 8compliant Python code for data processing and pipeline development.

- Expertlevel SQL skills (window functions, CTEs, complex joins, query plan analysis).

- Direct production experience configuring and running dbt Core or dbt Cloud.

- Proven track record designing dimensional models (Star schema, Snowflake schema, One Big Table approaches).

- Engineering Standards : Strong grasp of software engineering fundamentals applied to data (CI/CD, code reviews, automated unit/integration testing, environment management).

Soft Skills :

Clear communication skills with the ability to explain complex technical concepts to nontechnical stakeholders.

Strong problemsolving mindset and ownership of data reliability from ingestion to consumption.

Job Responsibilities :

- Pipeline Development & Maintenance : Architect, build, and maintain scalable, reliable batch and streaming data ingestion pipelines from diverse internal and thirdparty sources using Python and cloudnative services.

- Data Transformation & Modeling : Develop, test, and maintain modular, versioncontrolled data transformation models using dbt and complex SQL, following modern analytics engineering best practices.

- Data Warehouse Optimization : Monitor, finetune, and optimize cloud data warehouses (primarily Google BigQuery) for query speed, concurrency, storage efficiency, and cost management.

- Data Quality & Governance : Establish automated data quality frameworks, testing suites, alerting mechanisms, and documentation (e.g., dbt tests, Great Expectations) to guarantee data accuracy, schema integrity, and pipeline uptime.

- Orchestration & Workflow Automation : Implement and maintain robust orchestration DAGs (e.g., Apache Airflow / Cloud Composer) with proactive alerting and dependency management.

- CrossFunctional Collaboration : Partner directly with data analysts, data scientists, and product engineers to translate technical and business requirements into productionready data assets and clear data contracts.

What We Offer :

- Exciting Projects : We focus on industries like HighTech, communication, media, healthcare, retail and telecom.

Our customer list is full of fantastic global brands and leaders who love what we build for them.

Collaborative Environment : You Can expand your skills by collaborating with a diverse team of highly talented people in an open, laidback environment - or even abroad in one of our global centers or client facilities!

WorkLife Balance : GlobalLogic prioritizes worklife balance, which is why we offer flexible work schedules, opportunities to work from home, and paid time off and holidays.

Professional Development : Our dedicated Learning & Development team regularly organizes Communication skills training(GL Vantage, Toast Master),Stress Management program, professional certifications, and technical and soft skill trainings.

Excellent Benefits : We provide our employees with competitive salaries, family medical insurance, Group