Top Data Engineer Jobs in Hyderabad

The Data Engineer will create data pipelines, extract data from systems, and convert customer requirements into technical solutions, utilizing ETL tools and SQL.

Lead design and implementation of scalable ETL/ELT pipelines, ensure data quality and governance, build dashboards and automated reporting, mentor engineers, troubleshoot production incidents, and improve platform reliability, performance, and observability to support analytics and business KPIs.

Lead and mentor a data engineering team to design, build, and manage scalable ETL/ELT pipelines on GCP. Build and optimize data lakes and BigQuery warehouses, develop batch and real-time processing (Dataflow, Pub/Sub), enforce code quality and CI/CD/DevOps best practices, and provide technical guidance for project planning and stakeholder collaboration.

Develop, enhance, and support ETL/data pipelines using Sparkola, PySpark and SQL. Build and manage batch and ad-hoc pipelines via Sparkola Job Server, use Cloudera Machine Learning for development, validate datasets for downstream analytics (QlikSense/Superset), engage stakeholders to translate requirements, support production issues, and follow JIRA-driven delivery and governance controls.

The Senior Snowflake Data Engineer will design, implement, and optimize data solutions in Snowflake, focusing on data warehousing, ETL/ELT, and orchestration using Python and Apache Airflow.

The Senior Snowflake Data Engineer will design and optimize data solutions on Snowflake, integrate ERP systems, develop ELT pipelines, and manage stakeholder requirements effectively. They require extensive experience in data warehousing and strong ERP knowledge.

Lead development and support of Honeywell's Informatica Product 360 PIM/MDM: oversee inbound/outbound jobs, analyze and implement change requests, perform code migrations and upgrades, build PIM modules and data quality customizations, configure Power BI reports, guide downstream integration, run demos with stakeholders, and contribute to AI automation.

Lead data engineering teams in building cloud-based data pipelines, optimize infrastructure performance, manage data quality, and support team development.

The Advanced Data Engineer implements data solutions for ERP migrations, ensuring data quality, mentoring teams, and managing projects for SAP deployments.

The Data Engineer will design and optimize data pipelines for the enterprise data warehouse, ensuring data quality, performance, and reliability while collaborating with stakeholders to meet data requirements.

The Data Engineer will build and maintain data pipelines and architectures, optimize data delivery processes, and support data-related technical issues while collaborating with stakeholders.

The Principal Data Engineer leads data engineering initiatives, designing and optimizing data platforms and pipelines, guiding adoption of technologies, mentoring teams, and aligning with business goals.

The role involves data modeling, troubleshooting complex issues, optimizing storage architectures and mentoring junior engineers while working with GCP and Python.

The Data Engineer will design, build, and maintain ETL pipelines and data products, utilizing big data technologies and ensuring efficient data architecture. Responsibilities include troubleshooting complex issues, developing scalable solutions, and managing databases and data security compliance.

Design and maintain scalable data pipelines using Azure technologies, optimize processing solutions, and collaborate with stakeholders for data solutions.

The Data Engineer will design and maintain data pipelines, ensuring reliability and performance across key tools like FiveTran and BigQuery while optimizing data platforms and supporting data-driven initiatives with cross-functional teams.

The Associate Data Engineer will assist in building and maintaining data pipelines, writing SQL queries, and ensuring data quality using tools like Snowflake and Matillion.

The Data Engineer role involves data analysis, creating data models, and collaborating with business partners. Applicants need strong technical and analytical skills, particularly in SQL and data modeling.

The FBS Data Engineer is responsible for acquiring, curating, and publishing data for analytical and operational purposes, creating ready-to-use data for consumers, and managing data projects of intermediate complexity with minimal supervision.

The Data Engineer will translate analytical requirements into scalable data products, handle data modeling in Snowflake using dbt, manage data pipelines with Airflow, ensure data quality, and collaborate with cross-functional teams.

The Senior Azure Data Engineer will design, develop, and maintain data infrastructure and pipelines, ensuring data quality, integrity, and alignment with business objectives. Responsibilities include collaborating with teams and establishing best practices for data engineering.

The role involves designing and building data infrastructure, developing ETL/ELT applications, collaborating with teams, and improving engineering processes for analytics and AI capabilities.

The Data Engineer will design and maintain data pipelines, support data workflows, optimize data platforms, and mentor team members to ensure high data quality and system resilience.

Design, build, test, and implement data products for finance (P&C insurance) use cases. Translate business data stories into technical requirements, perform data analysis and profiling, and deliver solutions using DBT, Snowflake, SQL, Python/PySpark, shell scripting, and Power BI within agile teams.

Responsible for designing and developing a GCP data ecosystem, creating data pipelines, optimizing data architectures, troubleshooting issues, and mentoring junior engineers.