Lead Platform Data Engineer

India - Bengaluru IT Capability Centre

Job Description

About Us:

Data and analytics excellence at Dyson is delivered by a diverse and collaborative global community, at the heart of that community is a hub team that enables all others: In Dyson’s Analytics Platform team, there has been significant investment into cloud technologies and tools; combined with an expansive scope and no shortage of ambition and momentum, Dyson Data Analytics Platform team is recognized throughout the organization to the highest level as critical to all of Dyson's strategic objectives. 

With a ‘one-team’ approach, the global community is on a mission to: 

  • Evolve existing solutions to stay ahead. 
  • Embed emerging solutions to capitalize on potential benefits. 
  • Deliver conceptualized & future solutions to introduce net-new capability. 

The Team 

As the Analytics Platform delivering the data, technology and community provision enabling Dyson’s global data and analytics capabilities, Dyson Analytics Platform team have end-to-end responsibility for the management of data platforms and integrations, enable our development and analytics teams to drive continuous features and capabilities for our customers, partners, and employees.  

Dyson Analytics platform team is a multi-disciplinary, global team providing round-the-clock development and operations - including platform architecture, engineering, management, DataOps, governance, and advance analytics expertise. 

Involved with every aspect of Dyson’s global business - from finance to product development, manufacturing to owner experience – the team is seeking to deliver solutions generating impressive and tangible business value. 

  

About the role: 

  • Providing technical leadership in Cloud Environments (like GCP, AWS) across Dyson and contributes to open-source Big Data technologies. 
  • Writing and tuning complex Data Pipelines, workflows, and data structures 
  • Adapting quickly to change in requirements and be willing to work with different technologies if required. 
  • Leading a Backend/Distributed Data Systems team while remaining hands-on is very important. 
  • Leading the effort to build, implement and support the data infrastructure in Cloud. 
  • Managing the business intelligence stakeholders, prioritize Data Platform projects according to business needs, and develops top-quality data products using industry best practices. 
  • Managing team of Data Platform engineers (both full-time engineers and/or partners) 
  • Owning deliverables for the Data and Analytics Platform team from a delivery perspective 
  • Leading in deployment, testing activities with hands on engineering and automation experience including CI/CD/CD and DataOps mindset 
  • Reviewing technical designs and providing feedback 
  • Designing and building end-to-end data solutions for analytics in GCP/AWS 
  • Migrating existing data pipelines into the Data platform 
  • Strengthening data quality and reliability through code 
  • Improving data lineage and governance by tagging through code 
  • Progressing standards and best practices for the platform and operational excellence 
  • Apply best practices and ways of working among our global Data Platform engineering team. 
  • Write clean code that can be easily understood by others. 

About you: 

  • Experience in Source control management such as Gitlab, Github, Bit Bucket 
  • Experience in Terragrunt for infrastructure as code, Apache Beam and Python for ELT (Extract Load Transform), Airflow for orchestration 
  • Hands-on in scripting languages, Java, Python, RDBMS (Oracle/MySQL) and Message queues 
  • Cloud Concepts and hands-on experience with Public Cloud Providers such as AWS, Azure, GCP 
  • Minimum 6 years of experience in managing one of GCP / AWS / Azure environment is a must. 
  • Minimum 4 years of experience architecting, designing, developing, and implementing cloud solutions on one of GCP / AWS / Azure platforms. 
  • Good cloud infrastructure technical knowledge including cloud security, cloud formation templates and cost optimization. 
  • Knowledge of information technology infrastructure domains such as compute server platforms, storage server platforms, server components, network devices, technologies and architectures, IT service delivery principles and best practices 
  • Familiarity with compliance & security standards across the enterprise IT landscape 
  • Experience using DevOps tools in a cloud environment, such as Ansible, Artifactory, Docker, GitHub, Jenkins, Kubernetes, Maven, and Sonar Qube 
  • Hands on experience in the following Cloud services is mandatory Google Big Query,Google Cloud Storage,Google Cloud Functions,Google Dataflow,Google Cloud SQL,Google Firestore,Google Cloud Composer,Google Compute Engine,Google App Engine,Google Kubernetes Engine,Google Cloud Run,Google Data Cataloge,Google Pub/Sub,Google Vertex AI,Terraform,Terragrunt,dbt,AWS Redshift,S3 Buckets,Lambda Functions,Azure Blob Storage,Azure Database SQL,Datadog 


Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity.

Apply now Apply later
  • Share this job via
  • or

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Airflow Ansible Architecture AWS Azure Big Data BigQuery Business Intelligence CI/CD Data Analytics Dataflow DataOps Data pipelines Data quality dbt DevOps Docker ELT Engineering Finance GCP GitHub GitLab Google Cloud Java Kubernetes Lambda Maven MySQL Open Source Oracle Pipelines Python RDBMS Redshift Security SQL Terraform Testing Vertex AI

Perks/benefits: Team events

Region: Asia/Pacific
Country: India
Job stats:  2  0  0

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.