27 days ago
Gurgaon, IndiaStaff+
Responsibilities
- Translate business requirements into scalable data architecture strategies and cloud solutions.
- Design and implement secure, high-performing Lakehouse architectures and data platforms using Databricks.
- Modernize legacy data systems and migrate them to cloud-based architectures.
- Design and implement data pipelines, data transformation, data integration, ETL, and streaming solutions.
- Implement data governance, data quality, data lineage, data privacy, compliance, and security practices.
- Optimize data platforms for performance, scalability, and cost efficiency while monitoring and troubleshooting issues.
- Collaborate with stakeholders, data engineers, data scientists, business users, and technical teams.
- Provide guidance and mentorship to junior team members and act as a data architecture subject matter expert.
- Lead and coordinate medium- to large-scale RFP responses, develop technical solutions, and present them to clients.
- Groom team members in pre-sales activities.
Requirements
- In-depth experience designing and implementing scalable, secure, high-performing cloud Lakehouse architectures using Databricks.
- Proficiency with AWS, Microsoft Azure, or Google Cloud Platform and their data services.
- Expertise modernizing legacy data systems and transitioning them to cloud architectures.
- Strong understanding of ETL, data pipelines, data streaming, and data integration using Python, Kafka, PySpark, dbt, cloud ETL services, SQL, and PL/SQL.
- Familiarity with relational and non-relational databases, data lakes, and data warehouses.
- Strong hands-on knowledge of data modeling using ERwin.
- Knowledge of data governance, data quality, data lineage, data privacy, compliance, encryption, access controls, and data masking.
- Proficiency in Python, Java, or Scala, plus scripting with SQL or Shell.
- Ability to lead or coordinate medium- to large-scale RFPs and articulate end-to-end big-data and analytics solutions in PowerPoint or Word documents.
- Excellent communication and collaboration skills with stakeholders, business users, and technical teams.
- At least one Databricks certification at the Associate or Professional level is mandatory.
- Preferred experience includes hybrid-cloud exposure and end-to-end data architecture experience.
- A bachelor's degree in Business Analytics, Computer Science, or Statistics, or a master's degree in Data Science.
- English proficiency at C2 level is required; listed preferred certifications include data management, Databricks, Azure Data Engineer, and Oracle Database certifications.
Benefits
- Regular full-time employment with a hybrid work arrangement.
- Flexible work time in India.
- Hands-on experience, mentorship, and learning opportunities.
- Opportunity to lead AI-powered transformation and work on enterprise business challenges.
Tech Stack
Categories
Data Engineering
About Genpact
Genpact is a global professional services and technology firm that runs and transforms mission-critical operations for large enterprises through consulting, managed services, and AI- and analytics-driven platforms. It serves industries such as banking, insurance, healthcare, and manufacturing/supply chain, modernizing finance, risk, customer service, and back-office processes. Headquartered in New York and listed on the NYSE (G), Genpact originated within GE before becoming an independent public company.