Top Data Engineer Jobs in Hyderabad

Design and implement data federation and lakehouse architectures (Starburst/Trino), build scalable ETL/ELT pipelines using Python and Spark, optimize Spark and federated queries, manage Delta/Iceberg/Hudi tables, and enforce governance, access control, and data masking for analytics and AI use.

The Lead Data Engineer will design and implement data architectures, manage data pipelines and integration solutions, ensure data quality, and provide mentorship to junior members while collaborating with stakeholders on data requirements and reporting.

The Data Visualization Developer will create and support dashboards in Power BI, develop SQL scripts, perform regression testing, and troubleshoot existing scripts.

As a Senior Data Engineer, you will develop and maintain data pipelines for healthcare data, ensuring data quality, reliability, and adherence to enterprise standards while collaborating with architects and stakeholders.

Lead the modeling of the Customer Data Platform, defining event taxonomy and ensuring reliable datasets for analytics, product insights, and machine learning. Collaborate with various teams to maintain data consistency and shape the architecture of the behavioral data platform.

The Senior Data Engineer will design and maintain pipelines for event data ingestion and validation, ensuring operational reliability and consistency for analytics.

The Senior Data Engineer will develop data ingestion, transformation, and enrichment pipelines, ensuring data quality and reliability. Responsibilities include creating Bronze and Silver data layers, using SQL and dbt for implementation, and collaborating with architects and stakeholders to align data solutions with enterprise standards.

The Senior Data Engineer will design and build data infrastructure and pipelines, enhance AI capabilities, and collaborate with teams on data solutions while mentoring junior engineers.

Design, develop and integrate data products and pipelines on GCP. Collaborate with engineers, data scientists and SMEs to deliver medium-scale projects, improve data governance and IT security processes, coach team members, and coordinate cross-team schedules to meet business priorities.

Lead design, development, integration and testing of data products. Manage and operate data and knowledge management systems, coordinate cross-team project delivery, analyze data to inform business impact, suggest process and IT security improvements, and coach team members.

Design, develop, integrate, and test data product features; collaborate with Data Ops, Software Engineers, Data Scientists and SMEs; manage significant aspects of data management systems; identify and implement process and security improvements; deliver medium-scale projects; coordinate cross-team schedules; analyze multi-source data and coach colleagues.

Design, build, test and operate data products and backend microservices for Agentic AI use cases. Work with cross-functional teams to produce well-tested code, provision curated data in GCP, implement pipelines (Airflow), and ensure data governance, architecture and lifecycle management within agile, DevOps-driven delivery.

Design, develop, integrate and test data product features in collaboration with Data Ops, Software Engineers, Data Scientists and business SMEs. Manage medium-scale projects, identify improvements in data and security processes, coordinate cross-team schedules, coach peers, analyse business impacts using diverse data sources, and deliver data management solutions aligned to product roadmaps.

Design, develop, integrate and test data product features using GCP data services. Collaborate with engineers, data scientists and business SMEs, deliver medium-scale projects, improve processes, and coach others while identifying and implementing operational and security improvements.

Support and validate bank data migrations: maintain trackers, perform data validation and reconciliations, manage defect logs, coordinate test data and cutover/mock runs, prepare audit evidence, and produce status dashboards.

Lead and govern bank data migration workstream: define migration strategy and cutover approach, develop migration plans and mock runs, validate source-to-target mappings, oversee vendor ETL/designs, execute reconciliation and verification controls, manage defect triage and test data readiness, ensure data governance/security compliance, and report progress and risks to program stakeholders.

Support and validate data migration activities for legacy-to-modern core banking projects: maintain mapping and migration trackers, perform data validation and reconciliations, manage exception logs, coordinate SIT/UAT test data readiness, produce status dashboards, and support cutover/mock runs while ensuring data security and audit artifacts.

The Senior Data Migration Developer will manage Workday data migrations, collaborating with clients to design solutions, ensure data quality, and support cutover execution.

Design, build, and maintain data ingestion pipelines (Fivetran) into Snowflake, transform raw data into analytics-ready models, and create Tableau dashboards to track financial and GTM metrics. Partner with Finance and stakeholders to define KPIs, validate and reconcile metrics across CRM/ERP systems, manage Snowflake objects and governance, analyze revenue and usage trends, and improve analytics workflows and self-service reporting.

Lead development and execution of data governance policies, standards, and metadata repositories. Collaborate with stakeholders and data stewards, monitor and automate data quality metrics and KPIs, provide governance guidance to projects, run education sessions, and support risk/issue management and project planning.

The Data Engineer will design and optimize data pipelines using Snowflake and DBT, ensuring data quality and supporting cloud-based data solutions.

Build and maintain large-scale PySpark/Spark data reconciliation pipelines on Hadoop/Big Data platforms; integrate with Kafka, APIs and microservices; support capital markets regulatory reporting and reconciliations; lead globally distributed teams, manage stakeholders, and deliver solutions with strong application design and optional UI integration.

Design, build, optimize, and deploy large-scale Spark/Scala data processing and ETL pipelines on Cloudera (CDH). Collaborate with data teams, ensure data integrity and security, troubleshoot performance, and implement version control and CI/CD for Spark applications.

Design, build, and optimize end-to-end data pipelines for large structured and unstructured data. Implement near-real-time ETL, data validation, monitoring, and performance optimization. Collaborate with stakeholders, document designs and workflows, and provide technical guidance to the team.

Design, implement, and optimize Apache DolphinScheduler workflows and ETL pipelines. Integrate with Hadoop, Spark, Flink, Hive, and Kafka. Develop custom plugins, troubleshoot performance and scalability issues, monitor job execution and resource allocation, and maintain CI/CD, version control, and infrastructure automation while collaborating with data engineers and DevOps teams.