Lead the implementation of cloud-based solutions using major platforms such as Google Cloud Platform and Microsoft Azure, automating CI/CD pipelines and optimizing cloud infrastructure for data-intensive workloads.
Responsibilities
Automate integration and continuous deployment processes using DevOps tools (Git, Terraform, Ansible, Kubernetes).
Design and develop complex, high-performance data pipelines on cloud platforms (DataProc, BigQuery, Cloud Functions, MS Fabric, DataBricks, DataFactory).
Optimize cloud infrastructure for scalable data processing while applying FinOps principles.
Collaborate with cross‑disciplinary teams (Data Science, IT, business) to understand functional and technical needs.
Maintain technological watch to integrate best practices in Data Engineering and Cloud.
Design and build complex ETL/ELT pipelines for structured and unstructured data sources using GCP native services like Cloud Storage, Dataflow, and Dataproc, Data Integration & ETL/ELT
Build and orchestrate automated data pipelines using Fivetran, Google DTS, and custom ETL/ELT frameworks
Create robust ingestion patterns for batch and streaming data
Troubleshoot data integration issues, latency problems, and pipeline failures
Partner with application teams to integrate SaaS, on-prem, and cloud sources
Requirements
Bachelor’s degree in computer science, Information Systems, or related field.
A Staff Data Engineer role focused on leading design and architecture of scalable data platforms on GCP, managing engineering teams, and driving data strategy roadmaps.
Locations (2)
Bangalore, Karnataka, India
Chennai, Tamil Nadu, India
Responsibilities
Lead the design and architecture of scalable, resilient, and high-performance data platforms on Google Cloud (GCP).
Define and implement data engineering best practices, including data modeling, pipeline orchestration, and data governance.
Architect solutions using Big Data technologies such as Apache Spark, Hadoop ecosystem, and distributed systems.
Ensure alignment to enterprise data strategy, including data products, SSoT, and platform standardization.
Drive end-to-end data pipeline development using Scala, Spark, and modern ETL/ELT frameworks.
Senior Data Engineer responsible for designing, building, and maintaining scalable data platforms on Google Cloud.
Responsibilities
Implement the design and architecture of scalable, resilient, and high-performance data platforms on GCP
Implement data engineering best practices, including data modeling, pipeline orchestration, and data governance
Develop solutions using Big Data technologies such as Apache Spark, Hadoop ecosystem, and distributed systems
Drive end-to-end data pipeline development using Scala, Spark, and modern ETL/ELT frameworks
Lead development of batch and real-time data processing pipelines leveraging GCP services like BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Storage
Lead design, architecture, and delivery of scalable data platforms on Google Cloud, manage a team of data engineers, and drive data strategy and modernization initiatives.
Locations (2)
Bangalore, India
Chennai, Tamil Nadu, India
Responsibilities
Lead the design and architecture of scalable, resilient, and high-performance data platforms on GCP
Define and implement data engineering best practices, including data modeling, pipeline orchestration, and data governance
Architect solutions using Big Data technologies such as Apache Spark, Hadoop ecosystem, and distributed systems
Drive end-to-end data pipeline development using Scala, Spark, and modern ETL/ELT frameworks
Lead development of batch and real-time data processing pipelines leveraging GCP services
En tant qu'Expert Devops, vous aurez un rôle central dans la mise en œuvre de solutions basées sur les principales plateformes Cloud (GCP, Azure) eterez les clients dans la transformation de leurs données.
Responsibilities
Automatiser les processus d’intégration et de déploiement continu via des outils DevOps (Git, Terraform, Ansible, Kubernetes)
Concevoir et développer des pipelines de données complexes et performants sur les plateformes Cloud (DataProc, BigQuery, Cloud Functions, MS Fabric, DataBricks, DataFactory)
Optimiser les infrastructures cloud pour la gestion et le traitement de grandes volumétries de données (FinOps)
Collaborer avec des équipes pluridisciplinaires (Data Science, IT, métiers)
Assurer une veille technologique pour intégrer les meilleures pratiques en Data Engineering et Cloud
Requirements
Diplôme de type Ingénieur ou Bac+5 en Informatique
Software Engineer focused on Enterprise Search platform at AutoZone
Responsibilities
Develop and enhance e-commerce search capabilities using Elasticsearch
Develop and maintain scalable indexing and data-processing pipelines using Apache Spark and GCP services such as Dataproc and Dataflow
Improve search relevance, ranking, filtering, faceting, autocomplete, and product discovery experiences across e-commerce platforms
Partner with product managers, business stakeholders, and cross-functional engineering teams to understand search requirements and translate them into high-quality technical solutions
Develop low-level designs (LLDs) for assigned features and participate with architects and senior engineers in establishing high-level designs (HLDs) and technical approaches
Requirements
Bachelor’s or master's degree in computer science, Software Engineering, Information Systems, or related field
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