Senior Data Consultant

Senior Data Consultant (Analytics Engineering)

Location:Hybrid (London – Office Days: Tuesday & Thursday)

Company:Fast-growing Data & Analytics Platform

Salary:£65,000 - £85,000

Company Overview

They are a rapidly growingdata and analytics platformfocused on helping businesses centralise and streamline their data. TheirETL-driven platformintegrates machine learning and data science tools to support data-driven decision-making. Serving clients across various industries, includingB2B SaaS,retail, andcharity, they specialise in building scalable data infrastructures and delivering actionable insights.

With a strong emphasis on financial data, their team is dedicated to enabling clients to make more informed decisions by creating a single source of truth and optimising their data processes. Theyre expanding quickly and offer exciting opportunities for individuals passionate about data engineering, analytics, and cloud technologies.

Role Overview

We are seeking a Senior Data Consultant to help companies centralize their data using an ETL-driven decision intelligence platform with integrated machine learning and data science capabilities. This role will be instrumental in developing scalable data infrastructure and enabling clients to make data-driven decisions.

Key Responsibilities

• Build asingle source of truthfor clients by structuring and modeling data.
• Developscalable data pipelinesintegrating financial, customer, CRM, ERP, and marketing data.
• Deliver end-to-enddata modellingprojects, connecting multiple sources and creatingmetrics/KPIs.
• Work primarily withSQL, dbt, and cloud data warehouses(Snowflake, BigQuery, Redshift).
• UtilizePower BI/Tableaufor reporting.

Technical Requirements

Essential

• Strong proficiency in SQLwith the ability to write complex queries, optimise performance, and manipulate large datasets efficiently. This includes expertise in database management, data extraction, transformation, and analysis, ensuring seamless data workflows for all stakeholders.
• Working withmodern cloud data warehousessuch asSnowflake,BigQuery, orRedshift. You should be comfortable creating robust data models, building scalable pipelines, and ensuring data quality within these cloud environments.

Desirable

• Experience with dbt (Data Build Tool), particularly in managing and automating data transformation.
• Solid understanding ofPython, especially in the context of automating data processes, integrating APIs, and implementing machine learning models to enhance data analysis capabilities. Experience with Python libraries like Pandas or NumPy is a plus.
• Practical experience working with keyfinancial metrics, including revenue, retention, churn, and customer lifetime value, along with a deep understanding of how to extract actionable insights from these data sets to drive business decisions.
• Demonstrated ability tointegrate diverse data sources seamlessly, ensuring smooth data flow across systems, and combining financial, operational, and customer data to create a unified view for accurate reporting and analysis.