At a Glance
- Tasks: Transform data pipelines from SAS to Python and DBT for Snowflake.
- Company: Join a forward-thinking tech company in London or Edinburgh.
- Benefits: Flexible working options, competitive pay, and opportunities for growth.
- Other info: Exciting projects with a dynamic team and career advancement potential.
- Why this job: Be at the forefront of data engineering and make a real difference.
- Qualifications: Experience with SAS, Python, DBT, and data management in Snowflake.
The predicted salary is between 60000 - 80000 £ per year.
We are currently recruiting for a Senior Data Engineer (SAS). You will rewrite existing pipelines (SAS, Info, pearl, shell scripts) to target state which will be Python and DBT transformation based to be then loaded to SF on Azure.
Skills:
- SAS (primary)
- pearl, shell scripts (secondary)
- Experience converting to Python, DBT based pipelines and loading data to Snowflake
- Data management experience in Snowflake with expertise in Python, DBT, Airflow or similar technologies
- Hands-on experience in DBT & SQL Snowflake (added advantage)
If you feel you have the skills and experience needed for this role; please do apply now.
Job Location: London & Edinburgh
Job type: Full Time, Permanent, Contract
Senior Data Engineer: SAS to Python/DBT on Snowflake employer: Parker Shaw
Join a forward-thinking company that values innovation and collaboration, offering a dynamic work culture where your contributions as a Senior Data Engineer will directly impact our data transformation initiatives. With opportunities for professional growth and development in the vibrant cities of London and Edinburgh, you will be part of a team that embraces cutting-edge technologies like Python and DBT, ensuring you stay at the forefront of the industry. Enjoy competitive benefits and a supportive environment that fosters creativity and excellence.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer: SAS to Python/DBT on Snowflake
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with Python and Snowflake. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving SAS to Python conversions or DBT transformations. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with Snowflake, DBT, and any relevant tools. Practising common interview questions can help you feel more confident when it’s your turn to shine.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented folks like you. Plus, applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Senior Data Engineer: SAS to Python/DBT on Snowflake
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with SAS, Python, and DBT. We want to see how your skills match the job description, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for the Senior Data Engineer role. Share your passion for data engineering and how your background aligns with our needs.
Showcase Your Technical Skills:When filling out your application, be specific about your technical skills. Mention your hands-on experience with Snowflake, Airflow, and any other relevant technologies. We love seeing candidates who can hit the ground running!
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!
How to prepare for a job interview at Parker Shaw
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially SAS, Python, and DBT. Brush up on your knowledge of Snowflake and SQL too, as they’ll likely come up during the interview.
✨Showcase Your Pipeline Experience
Be ready to discuss specific examples of how you've rewritten data pipelines in the past. Highlight any challenges you faced and how you overcame them, particularly when converting from SAS to Python or DBT.
✨Prepare for Technical Questions
Expect technical questions that test your understanding of data engineering concepts. Practice explaining your thought process clearly, especially around data management and transformation techniques.
✨Ask Insightful Questions
At the end of the interview, have a few thoughtful questions prepared about the team’s current projects or the company’s approach to data engineering. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
