Analytics Engineer

Jobgether • Nigeria

Remote

This Job is No Longer Active This position is no longer accepting applications

AI Summary

Jobgether is seeking an Analytics Engineer to design, build, and maintain data infrastructure. The ideal candidate will have 3+ years of experience in analytics engineering, data analytics, or BI development. The role requires expertise in SQL, dbt, and Python, with a strong understanding of ETL/ELT and data warehousing concepts.

Key Highlights

Design, build, and maintain data infrastructure

Transform raw data into reliable datasets

Collaborate with analysts and engineers to ensure data accuracy and consistency

Key Responsibilities

Design, develop, and maintain data models aligned with business needs and data architecture standards

Build, manage, and optimize end-to-end data pipelines

Implement data validation, quality checks, and monitoring

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Technical Skills Required

SQL dbt Python ETL/ELT data warehousing

Benefits & Perks

Competitive salary within the €80K – €100K range

Flexible remote-first work environment

30 days of PTO and annual team offsites

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Nice to Have

Knowledge of blockchain data structures and on-chain analytics

Familiarity with cloud data warehouses (e.g., Snowflake) and data architecture concepts

Job Description

As an Analytics Engineer, you will design, build, and maintain the end-to-end data infrastructure that powers business insights and decision-making. You will transform raw data from multiple sources, including internal databases, APIs, and blockchain networks, into reliable, well-modeled datasets that inform strategy and operations. Collaborating closely with analysts, engineers, and cross-functional stakeholders, you will ensure data accuracy, consistency, and accessibility. Your work will directly impact the quality of analytics, dashboards, and reporting, while supporting exploratory analyses and on-chain data investigations. This role offers the opportunity to operate in a fast-moving, remote-first environment, taking ownership of complex data challenges and contributing to process improvements across the team.

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