EY - GDS Consulting - AI And DATA -AI Data Platform Engineer - Snowflake- Senior
Ernst and Young12 hours ago
Bengaluru, IndiaSenior
Responsibilities
- Design, develop, and optimize scalable data pipelines, ingestion frameworks, and Aladdin inbound and outbound integration solutions.
- Perform data discovery, source analysis, data mapping, asset alignment, reconciliation, and data parity validation for client onboarding.
- Build batch, streaming, API-driven, event-based, CDC, and file-based ingestion frameworks.
- Create curated, analytics-ready, and AI-ready data products with quality controls, lineage, metadata management, and governed consumption.
- Implement data quality, validation, audit, reconciliation, compliance, reporting, and operational control frameworks.
- Develop reusable onboarding accelerators, metadata-driven frameworks, pipeline templates, monitoring solutions, and operational support capabilities.
- Design workflow orchestration, scheduling, dependency management, and cross-platform integrations.
- Optimize Spark, SQL, cloud-native, and distributed processing workloads for performance, scalability, reliability, and cost efficiency.
- Implement Git-based engineering, CI/CD, infrastructure-as-code, automated testing, deployment automation, and environment promotion.
- Integrate enterprise platforms with APIs, cloud services, governance solutions, security controls, metadata platforms, and analytics consumers.
- Apply AI, GenAI, and agentic AI capabilities to metadata discovery, documentation, data quality monitoring, anomaly detection, and operational intelligence.
- Support semantic search, RAG, intelligent data discovery, conversational analytics, and enterprise knowledge retrieval solutions.
- Implement governance, security, privacy, lineage, audit logging, access controls, and policy-driven data management.
- Build metadata-driven audit, monitoring, observability, and Data SRE capabilities for pipeline health, data quality, incidents, lineage, performance, and SLA/SLO adherence.
- Support cloud deployment, application registration, platform onboarding, environment management, and operational readiness.
- Contribute to technical design reviews, platform standards, engineering best practices, automation initiatives, and continuous improvement.
- Mentor engineers and collaborate with architects, security teams, SRE teams, client teams, and BlackRock stakeholders.
Requirements
- 5–10 years of experience in data engineering, data platform operations, analytics engineering, platform engineering, or AI platform enablement.
- Strong hands-on implementation experience with cloud data platforms, APIs, Git connectivity, CI/CD, governed access patterns, SRE practices, and production operations.
- Experience designing and supporting large-scale data integration, onboarding, reconciliation, data quality, compliance, and reporting solutions.
- Experience with Databricks, Snowflake, Microsoft Fabric, Spark, lakehouse architectures, data warehouses, data lakes, semantic data products, and enterprise data integration.
- Experience or exposure to Aladdin data onboarding and integration, investment data management, asset alignment, data mapping, parity validation, and reconciliation.
- Experience with Python, PySpark, SQL, Snowpark, APIs, Git, dbt, data modeling, unit testing, integration testing, and data pipeline testing.
- Experience with Cortex AI, Databricks AI/BI and Genie, Mosaic AI, Fabric Copilot, vector search, RAG, Graph RAG, agentic AI, semantic retrieval, and LLMOps is relevant to the role.
- Experience with Azure, AWS or GCP, Terraform or OpenTofu, Kubernetes, Docker, GitHub Actions, Azure DevOps, Jenkins, infrastructure-as-code, policy-as-code, Azure Data Factory, Databricks Workflows, Fabric Pipelines, and enterprise orchestration tools.
- Preferred qualifications include investment data and BlackRock Aladdin integration experience, relevant cloud/platform, data engineering, DevOps, security, governance, and AI/ML engineering certifications, architecture awareness, delivery ownership, and mentoring ability.
Benefits
- Support, coaching, and feedback from engaging colleagues.
- Opportunities to develop new skills and progress your career.
- Individual progression planning, education, coaching, and practical experience.
- Freedom and flexibility to handle the role in a way that is right for you.
- Work in an interdisciplinary environment emphasizing quality and knowledge exchange.
- Opportunity to work on varied projects for start-ups and Fortune 500 companies.
Tech Stack
Apache SparkAWSAzureDatabricksdbtDockerGitGitHub ActionsGoogle Cloud PlatformJenkinsKubernetesPythonSnowflakeSQLTerraform
Categories
Data Engineering
About Ernst and Young
Ernst & Young (EY) provides audit/assurance, tax, consulting, strategy and transactions services to enterprises, financial institutions, and public‑sector clients. Structured as a global network of partner‑owned member firms, it sells professional services on a fee basis, including a dedicated Financial Services Organization for banking, insurance, and capital markets. Headquartered in London, EY was formed in 1989 from the merger of Ernst & Whinney and Arthur Young, and operates in 150+ countries.