Senior Analytics Engineer - Remote - 35 To 50 lacs

This is an URGENT requirement. We are hiring for a UK based Fintech company (name is kept confidential). The company is seeking a talented Senior Analytics Engineer to join the team and help build analytics pipelines working closely with the senior stakeholders. As an Analytics Engineer specializing in the payments space, youll be at the forefront of analysing payment transaction data, uncovering trends, and optimising card issuance operations. Your work will directly shape strategic initiatives and improve business outcomes.

Data Build Tool (DBT)

DBT

Key Responsibilities

• Analyze large datasets related to payment processing and customer transactions to uncover trends and actionable insights.
• Develop dashboards and reports to track KPIs and support decision-making.
• Work with stakeholders to understand data needs and provide insights through presentations and reports.
• Deliver data-driven recommendations to support business objectives.
• Build and optimize data pipelines using dbt, ensuring clean and accessible data.
• Monitor data quality and implement validation processes in collaboration with data engineers.
• Create scalable data models in Snowflake using dbt and identify opportunities for efficiency gains.
• Optimize workflows and monitor system performance for continuous improvements.
• Ensure data practices meet regulatory standards and assist in compliance reporting.
• Stay updated on industry trends and contribute to process enhancements.

Qualifications

• Bachelors degree in Data Science, Computer Science, Information Systems, Finance, or a related field.
• Proven experience as a Data Analyst/Analytics Engineer role, preferably in the payments industry with issuer processors.
• Proven experience in SQL, DBT and Snowflake.
• Proficiency in building and managing data transformations with dbt, with experience in optimizing complex transformations and documentation.
• Hands-on experience with Snowflake as a primary data warehouse, including knowledge of performance optimization, data modeling, and query tuning.
• Strong proficiency in data analysis tools and languages (e.g., SQL, Python).
• Strong understanding of data modeling principles and experience applying modeling techniques.
• Proficiency with data visualization tools such as Tableau, Power BI, or similar.
• Knowledge of payment processing system, card issuance, and related services.
• Experience with cloud-based data solutions (e.g., AWS, Azure, Google Cloud).
• Familiarity with modern data architecture such as data Lakehouse.
• Strong analytical, problem-solving, and communication skills.
• Attention to detail and a commitment to data quality and integrity.
• Familiarity with regulatory requirements and security standards in the financial industry