10 hours ago

Lead, Data Engineering

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 10 hours agoStatus: Live

Job Summary

Lead and support an offshore team in migrating and operating enterprise data pipelines within a Databricks-on-AWS lakehouse environment. Own data onboarding, including Bronze/Silver/Gold layer standardization, metadata-driven workflows, and secure governed access using AWS and Databricks tooling. Troubleshoot pipeline issues, collaborate on data quality and lineage controls, and drive operational excellence through monitoring, incident management, CI/CD, and cloud-native orchestration.

Location: Hyderabad, Chennai

Workplace: Hybrid

Employment Type: Full time

Job Function: Administration & Executive Assistance

Seniority: Manager level

Key Responsibilities

•Migrate existing data pipelines to the Databricks platform and support ongoing operation, troubleshooting, and optimization post-migration.
•Support data onboarding for new assets using standardized processes and help standardize Bronze/Silver/Gold lakehouse layers.
•Manage metadata-driven onboarding workflows using AWS Glue Data Catalog and Databricks governance capabilities.
•Collaborate on platform integration support, including data quality checks, metadata management, reconciliation, and auditability/lineage controls.
•Ensure operational excellence through deployment, monitoring, incident management, documentation, and delivery practices (CI/CD, release management, and observability).

Pay and Benefits

Perks:Health InsuranceRetirementLearning BudgetPaid LeaveStudent Loan

Key Requirements

•5+ years of experience in data engineering, pipeline development, or related roles.
•Proven experience supporting data onboarding, migration, and pipeline operations, including ongoing troubleshooting and optimization.
•Hands-on expertise with data engineering tools such as Spark, SQL, and Python.
•Experience working with Databricks (or similar cloud data platforms) and enterprise AWS data engineering services like Amazon S3 and AWS Glue.
•Strong understanding of secure data access, governance, and data quality/metadata/lineage concepts.

Experience:5+ yearsData engineeringData pipelinesDatabricksAWSLakehouse

Skills:Problem-solvingCommunicationCollaborationTroubleshootingMentoring

Certifications:DatabricksAWS

Tech Stack:DatabricksSparkSQLPythonPySparkAmazon S3AWS GlueAWS IAMAWS Lake FormationDatabricks Unity CatalogUnity CatalogDelta LakeApache IcebergAmazon AthenaAmazon CloudWatchCI/CDInfrastructure as codeAWS Step FunctionsAWS LambdaAmazon Kinesis

Company Brief

S&P Global

Provides financial information, analytics, benchmarks, and credit ratings to markets and institutions worldwide, offering data, research, indices, and risk assessment tools across the financial services and commodities sectors.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: New York, United States

Founded: 1917

Website LinkedIn

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S&P Global

10 hours ago

Lead, Data Engineering

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 10 hours agoStatus: Live

Job Summary

Location: Hyderabad, Chennai

Workplace: Hybrid

Employment Type: Full time

Job Function: Administration & Executive Assistance

Seniority: Manager level

Key Responsibilities

•Migrate existing data pipelines to the Databricks platform and support ongoing operation, troubleshooting, and optimization post-migration.
•Support data onboarding for new assets using standardized processes and help standardize Bronze/Silver/Gold lakehouse layers.
•Manage metadata-driven onboarding workflows using AWS Glue Data Catalog and Databricks governance capabilities.
•Collaborate on platform integration support, including data quality checks, metadata management, reconciliation, and auditability/lineage controls.
•Ensure operational excellence through deployment, monitoring, incident management, documentation, and delivery practices (CI/CD, release management, and observability).

Pay and Benefits

Perks:Health InsuranceRetirementLearning BudgetPaid LeaveStudent Loan

Key Requirements

•5+ years of experience in data engineering, pipeline development, or related roles.
•Proven experience supporting data onboarding, migration, and pipeline operations, including ongoing troubleshooting and optimization.
•Hands-on expertise with data engineering tools such as Spark, SQL, and Python.
•Experience working with Databricks (or similar cloud data platforms) and enterprise AWS data engineering services like Amazon S3 and AWS Glue.
•Strong understanding of secure data access, governance, and data quality/metadata/lineage concepts.

Experience:5+ yearsData engineeringData pipelinesDatabricksAWSLakehouse

Skills:Problem-solvingCommunicationCollaborationTroubleshootingMentoring

Certifications:DatabricksAWS

Company Brief

S&P Global

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: New York, United States

Founded: 1917

Website LinkedIn