At a Glance
- Tasks: Design and develop data pipelines for efficient data storage and analysis.
- Company: Join a leading firm committed to diversity and innovation.
- Benefits: Flexible work options, competitive salary, and wellness programmes.
- Why this job: Make an impact by optimising data systems and supporting AI and ML initiatives.
- Qualifications: Bachelor's degree in a relevant field and 6+ years of data management experience.
- Other info: Inclusive environment with opportunities for career growth and development.
The predicted salary is between 48000 - 72000 Β£ per year.
Job Description
Practice Group / Department: Application Centre β Canada
The Role
The Senior Data Engineer will be responsible for designing, developing, and maintaining the infrastructure and systems required for data storage, processing, and analysis. They play a crucial role in building and managing the data pipelines that enable efficient and reliable data integration, transformation, and delivery for all data users across the enterprise.
Key Responsibilities
- Designs and develops data pipelines that extract data from various sources, transform it into the desired format, and load it into the appropriate data storage systems
- Collaborates with data scientists and analysts to optimize models and algorithms for data quality, security, and governance
- Integrates data from different sources, including databases, data warehouses, APIs, and external systems
- Ensures data consistency and integrity during the integration process, performing data validation and cleaning as needed
- Transforms raw data into a usable format by applying data cleansing, aggregation, filtering, and enrichment techniques
- Optimizes data pipelines and data processing workflows for performance, scalability, and efficiency
- Monitors and tunes data systems, identifies and resolves performance bottlenecks, and implements caching and indexing strategies to enhance query performance
- Implements data quality checks and validations within data pipelines to ensure the accuracy, consistency, and completeness of data
- Takes authority, responsibility, and accountability for exploiting the value of enterprise information assets and of the analytics used to render insights for decision making, automated decisions and augmentation of human performance
- Works with board members and other executives to establish the vision for managing data as a business asset
- Establishes the governance of data and algorithms used for analysis, analytical applications, and automated decision making
Skills and Experience Required
- A bachelor\βs degree in computer science, data science, software engineering, information systems, or related quantitative field; masterβs degree advantageous.
- At least six years of work experience in data management disciplines, including data integration, modeling, optimization and data quality, or other areas directly relevant to data engineering responsibilities and tasks
- Proven project experience developing and maintaining data warehouses in big data solutions (Snowflake)
- Expert knowledge in Apache technologies such as Kafka, Airflow, and Spark to build scalable and efficient data pipelines
- Ability to design, build, and deploy data solutions that capture, explore, transform, and utilize data to support AI, ML, and BI
- Strong ability in programming languages such as Java, Python, and C/C++
- Ability in data science languages/tools such as SQL, R, SAS, or Excel
- Proficiency in the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure, GCP) and modern data warehouse tools (Snowflake, Databricks)
- Proficiency in the design and implementation of modern data architectures (ideally Azure, AWS. Microsoft Fabric, GCP, Data Factory) and modern data warehouse technologies (Snowflake, Databricks)
- Experience with database technologies such as SQL, NoSQL, Oracle, Hadoop, or Teradata
- Ability to collaborate within and across teams of different technical knowledge to support delivery and educate end users on data products
- Expert problem-solving skills, including debugging skills, allowing the determination of sources of issues in unfamiliar code or systems, and the ability to recognize and solve repetitive problems
- Excellent business acumen and interpersonal skills; able to work across business lines at a senior level to influence and effect change to achieve common goals.
- Ability to describe business use cases/outcomes, data sources and management concepts, and analytical approaches/options
- Ability to translate among the languages used by executive, business, IT, and quant stakeholders.
Diversity, Equity and Inclusion
To attract the best people, we strive to create a diverse and inclusive environment where everyone can bring their whole selves to work, have a sense of belonging, and realize their full career potential.
Our new enabled work model allows our people to have more flexibility in the way they choose to work from both the office and a remote location, while continuing to deliver the highest standards of service. We offer a range of family friendly and inclusive employment policies and provide access to programmes and services aimed at nurturing our people\βs health and overall wellbeing. Find more about Diversity, Equity and Inclusion here.
We are proud to be an equal opportunities employer and encourage applications from individuals who can complement our existing teams. We strive to create an inclusive and accessible recruitment process for all candidates. If you require any tailored adjustments or accommodations, please let us know here.
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Senior Data Engineer - Central Services employer: Norton Rose Fulbright
Contact Detail:
Norton Rose Fulbright Recruiting Team
StudySmarter Expert Advice π€«
We think this is how you could land Senior Data Engineer - Central Services
β¨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field and let them know you're on the lookout for opportunities. You never know who might have a lead or can put in a good word for you.
β¨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data pipelines and big data solutions. This will give potential employers a taste of what you can do and set you apart from the crowd.
β¨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with tools like Kafka, Airflow, and Snowflake, and how you've tackled challenges in past projects.
β¨Tip Number 4
Don't forget to apply through our website! It's the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior Data Engineer - Central Services
Some tips for your application π«‘
Tailor Your CV: Make sure your CV is tailored to the Senior Data Engineer role. Highlight your experience with data pipelines, integration, and any relevant technologies like Snowflake or Apache tools. We want to see how your skills match what we're looking for!
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 your background makes you a great fit for our team. Don't forget to mention any specific projects that showcase your expertise.
Showcase Your Technical Skills: In your application, be sure to highlight your technical skills, especially in programming languages like Java and Python, as well as your experience with cloud services. We love seeing candidates who can demonstrate their hands-on experience with the tools we use!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. Itβs super easy, and you'll be able to keep track of your application status. Plus, we love seeing applications come directly from our site!
How to prepare for a job interview at Norton Rose Fulbright
β¨Know Your Data Tools
Make sure you brush up on your knowledge of Apache technologies like Kafka, Airflow, and Spark. 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.
β¨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex data issues. Think about times when you had to debug unfamiliar code or systems, and be ready to explain your thought process and the solutions you implemented.
β¨Understand Business Use Cases
Be prepared to articulate how your technical skills translate into business outcomes. Familiarise yourself with the company's goals and think about how your experience can help achieve those objectives, especially in terms of data integration and quality.
β¨Emphasise Collaboration
Highlight your ability to work across teams with different technical backgrounds. Share examples of how you've collaborated with data scientists, analysts, and other stakeholders to optimise data pipelines and ensure data integrity.