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- Tasks: Design and optimise data pipelines, manage databases, and create insightful dashboards.
- Company: Join a forward-thinking company focused on data-driven solutions across various industries.
- Benefits: Enjoy flexible working options, competitive salary, and opportunities for professional growth.
- Why this job: Be part of a dynamic team that values innovation and collaboration in the tech space.
- Qualifications: 3-5 years in data engineering, strong SQL/NoSQL skills, and experience with ETL tools required.
- Other info: Work with cutting-edge technologies like AWS, GCP, and big data frameworks.
The predicted salary is between 36000 - 60000 £ per year.
We are seeking an experienced Data Engineer & Analytics Developer with 3 - 5 years of experience in designing and implementing data-driven solutions across various industries. The ideal candidate should have expertise in multiple database tools, ETL processes, and data analytics frameworks, with a strong ability to optimize, transform, and analyze large datasets for business insights.
Experience: 3 - 5 years
No of Openings: 01
Job Type: Full-time
Key Responsibilities:
- Data Engineering: Design, develop, and optimize data pipelines and ETL workflows to ensure efficient data flow and storage. Build and maintain scalable data warehouses, lakes, and marts using modern database technologies. Ensure data integrity, quality, and security while implementing industry best practices. Collaborate with software engineers, analysts, and stakeholders to define data requirements and architecture.
- Database Management: Manage and optimize SQL and NoSQL databases (PostgreSQL, MySQL, MongoDB, Cassandra, etc.). Design and implement data models to support business intelligence and analytics. Monitor, troubleshoot, and optimize database performance.
- Data Analytics & Reporting: Develop data visualizations and dashboards using tools like Power BI, Tableau, or Looker. Implement predictive analytics models to support business decision-making. Work with stakeholders to define KPIs and metrics for data-driven insights.
- Cloud & Big Data Solutions: Design and deploy data solutions on AWS, GCP, or Azure. Work with big data frameworks (Hadoop, Spark, Kafka) for real-time and batch processing. Implement serverless data processing where applicable.
Required Skills & Qualifications:
- 3 - 5 years of experience in data engineering and analytics development.
- Strong expertise in SQL, NoSQL databases, and data modeling.
- Hands-on experience with ETL tools (Apache Nifi, Talend, DBT, Airflow, Fivetran, etc.).
- Experience with data visualization tools (Tableau, Power BI, Looker).
- Proficiency in Python, R, or Scala for data manipulation and analytics.
- Experience with cloud-based data solutions (AWS Redshift, Snowflake, BigQuery, Azure Synapse).
- Familiarity with big data technologies (Apache Spark, Hadoop, Kafka).
- Understanding of data governance, security, and compliance best practices.
- Strong problem-solving and communication skills.
Data Analyst employer: Atharvasystem
Contact Detail:
Atharvasystem Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst
✨Tip Number 1
Network with professionals in the data engineering and analytics field. Attend industry meetups, webinars, or conferences to connect with potential colleagues and learn about the latest trends and technologies. This can help you gain insights into what we at StudySmarter value in candidates.
✨Tip Number 2
Familiarise yourself with the specific tools and technologies mentioned in the job description. If you haven't worked with certain ETL tools or cloud platforms, consider taking online courses or tutorials to boost your skills. Demonstrating proficiency in these areas will make you a more attractive candidate for us.
✨Tip Number 3
Prepare to discuss your past projects and experiences in detail during the interview. Be ready to explain how you designed data pipelines, optimised databases, or created visualisations. We appreciate candidates who can articulate their contributions and the impact of their work on business outcomes.
✨Tip Number 4
Stay updated on the latest developments in data governance and compliance. Understanding these aspects is crucial for our role, as we prioritise data integrity and security. Being knowledgeable in this area will show us that you are serious about the responsibilities that come with the position.
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering and analytics development. Focus on your expertise with SQL, NoSQL databases, and any ETL tools you've used. Use specific examples to demonstrate your skills in designing data pipelines and optimising database performance.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data analytics and your understanding of the company's needs. Mention your experience with cloud-based solutions and big data technologies, and explain how you can contribute to their data-driven decision-making processes.
Highlight Relevant Projects: Include specific projects in your application that demonstrate your ability to develop data visualisations and dashboards. Discuss any predictive analytics models you've implemented and how they supported business decisions, as this will show your practical experience.
Showcase Soft Skills: In addition to technical skills, emphasise your problem-solving and communication abilities. Provide examples of how you've collaborated with stakeholders or worked within a team to define data requirements and architecture, as these skills are crucial for the role.
How to prepare for a job interview at Atharvasystem
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SQL, NoSQL databases, and ETL tools. Bring examples of projects where you've designed data pipelines or optimised database performance, as this will demonstrate your hands-on expertise.
✨Demonstrate Your Analytical Thinking
During the interview, highlight your problem-solving abilities by discussing specific challenges you've faced in data analytics. Use the STAR method (Situation, Task, Action, Result) to structure your responses and make them impactful.
✨Familiarise Yourself with Their Tech Stack
Research the company's use of cloud platforms and big data technologies. If they utilise AWS, GCP, or specific frameworks like Spark or Kafka, be ready to discuss your experience with these tools and how you can contribute to their projects.
✨Prepare Questions for the Interviewers
Engage with your interviewers by asking insightful questions about their data strategies, team dynamics, and future projects. This shows your genuine interest in the role and helps you assess if the company is the right fit for you.
