At a Glance
- Tasks: Design and implement data pipelines using GCP services for efficient data management.
- Company: Join a forward-thinking tech company with a hybrid work culture.
- Benefits: Enjoy competitive pay, flexible working, and opportunities for professional growth.
- Other info: Collaborate with diverse teams and enhance your skills in a supportive setting.
- Why this job: Make an impact by optimising data solutions in a dynamic environment.
- Qualifications: Experience in data engineering and proficiency in GCP required.
The predicted salary is between 36000 - 60000 £ per year.
Key Responsibilities
- Data Pipeline Development: Design and implement robust ETL/ELT pipelines using GCP services like Dataflow, Dataproc, Cloud Composer, and Data Fusion. Automate data ingestion from diverse sources (APIs, databases, flat files) into BigQuery and Cloud Storage.
- Data Modelling & Warehousing: Develop and maintain data models and marts in BigQuery. Optimize data storage and retrieval for performance and cost efficiency.
- Security & Compliance: Implement GCP security best practices including IAM, VPC Service Controls, and encryption. Ensure compliance with GDPR, HIPAA, and other regulatory standards.
- Monitoring & Optimization: Set up monitoring and alerting using Stackdriver. Create custom log metrics and dashboards for pipeline health and performance.
- Collaboration & Support: Work closely with cross-functional teams to gather requirements and deliver data solutions. Provide architectural guidance and support for cloud migration and modernization initiatives.
Skillset
- Technical Skills: Languages: Python, SQL, Java (optional). GCP Services: BigQuery, Dataflow, Dataproc, Cloud Storage, Cloud SQL, Cloud Functions, Composer (Airflow), App Engine. Tools: GitHub, Jenkins, Terraform, DBT, Apache Beam. Databases: Oracle, Postgres, MySQL, Snowflake (basic). Orchestration: Airflow, Cloud Composer. Monitoring: Stackdriver, Logging & Alerting.
- Certifications: Google Cloud Certified – Professional Data Engineer, Google Cloud Certified – Associate Cloud Engineer, Google Cloud Certified – Professional Cloud Architect (optional).
- Soft Skills: Strong analytical and problem-solving skills, excellent communication and stakeholder management, ability to work in Agile environments and manage multiple priorities.
Experience Requirements: Extensive experience in data engineering, strong hands-on experience with GCP, experience in cloud migration and real-time data processing is a plus.
Data Engineer employer: Cognizant
As a Data Engineer at our company, you will thrive in a dynamic hybrid work environment that fosters innovation and collaboration. We prioritise employee growth through continuous learning opportunities and provide access to cutting-edge GCP technologies, ensuring you stay ahead in your field. Our inclusive culture values diverse perspectives, making it an excellent place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨Network Like a Pro
Get out there and connect with folks in the data engineering space! Attend meetups, webinars, or even local tech events. You never know who might have the inside scoop on job openings or can refer you directly.
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those involving GCP services like BigQuery and Dataflow. Share it on platforms like GitHub or your personal website to give potential employers a taste of what you can do!
✨Ace the Interview
Prepare for technical interviews by brushing up on your Python and SQL skills. Practice common data engineering problems and be ready to discuss your experience with ETL pipelines and cloud services. Confidence is key!
✨Apply Through Us!
Don’t forget to check out our website for the latest job openings. Applying directly through us not only shows your interest but also gives you a better chance of landing that dream role in data engineering!
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with GCP services and data engineering. We want to see how your skills match the job description, so don’t be shy about showcasing your relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about data engineering and how you can contribute to our team. Keep it concise but engaging – we love a good story!
Show Off Your Technical Skills:When listing your technical skills, be specific! Mention your experience with Python, SQL, and any GCP services you’ve worked with. We’re looking for hands-on experience, so give us the details that matter.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at Cognizant
✨Know Your GCP Services
Make sure you brush up on your knowledge of GCP services like Dataflow, Dataproc, and BigQuery. Be ready to discuss how you've used these tools in past projects, as well as any challenges you faced and how you overcame them.
✨Showcase Your ETL/ELT Skills
Prepare to talk about your experience designing and implementing ETL/ELT pipelines. Have specific examples ready that demonstrate your ability to automate data ingestion from various sources and optimise data storage for performance and cost efficiency.
✨Highlight Security Practices
Familiarise yourself with GCP security best practices, including IAM and VPC Service Controls. Be prepared to discuss how you ensure compliance with regulations like GDPR and HIPAA in your previous roles.
✨Emphasise Collaboration
Data engineering is often a team effort, so be ready to share examples of how you've worked with cross-functional teams. Highlight your communication skills and how you've gathered requirements to deliver effective data solutions.
