Analytics Engineer (middle)

On-siteMidData Engineerposted recently

✦Role summaryAI-generated

This mid-level role focuses on designing scalable data pipelines and infrastructure to ensure seamless data flow and accessibility across inDrive’s operations, with a strong emphasis on Kubernetes and Terraform for cloud-native deployments. The candidate will collaborate cross-functionally to build robust APIs and automation tools, bridging data engineering with broader business decision-making.

Skills required

Kubernetes Terraform Data pipelines Api development Data validation Big data processing Unit testing Data infrastructure Data engineering Python ETL Spark SQL Flink

About this role

We’re looking for an Analytics Engineer to join our Data Engineering team.

Key Responsibilities

Foster a culture of working with data across the organization, ensuring data-driven decision-making
Create and maintain a unified system for processing, storing, and validating data, ensuring data integrity and accessibility
Design and build processes for processing and enriching data, participating in all stages of the data pipeline from data capture to consumer presentation
Develop and maintain infrastructure for big data storage and processing using tools like Kubernetes (K8S) and Terraform
Create and optimize APIs (REST, gRPC) for high-load data access services, enabling efficient data retrieval
Write integration and unit tests, develop automation tools for data validation and alerting
Сontribute to system design and architecture with the development team

Skills, Knowledge and Expertise

Advanced proficiency in Python 3.7+ with strong experience in developing ETL processes using PySpark
Proven experience in developing data flows using Airflow2
High level of expertise in SQL, including complex queries and optimization
Extensive knowledge and industrial experience with Kubernetes (K8S)
Strong understanding of data processing algorithms and principles, with experience in Spark/Flink
Solid understanding of general programming concepts, including design patterns, OOP, modularity, and pure architecture
Demonstrated ability to take ownership of technologies or services and proactively contribute ideas to the team