Data Engineer (Python, SQL, Airflow)

Everlytics is looking for a Data Engineer with advanced core programming, pipeline orchestration, and backend integration skills. We are looking for someone who excels at building robust data workflows, optimizing data movement, and handling large scale data systems using modern data engineering tools.
Technologies
Python (Advanced), SQL (Intermediate to Advanced), Apache Airflow, Apache Kafka.
Experience Required
1 to 3 years of proven hands-on data engineering experience, focusing heavily on designing, deploying, and maintaining production-grade data pipelines.
Solid background in writing clean, efficient Python code and complex SQL/ETL transformations to orchestrate large-scale data movement across batch and real-time processing systems.
Hands-on experience implementing real-time event-driven architectures and streaming pipelines using Apache Kafka for high-throughput data ingestion and consumption.
Expertise in building scalable, resilient data workflows using Apache Airflow for end-to-end task scheduling, monitoring, dependency management, and error handling.
Contributions in Technical Discussions with Enterprise Architects / Solution Architecture teams, specifically around workflow optimization, distributed data pipelines, and streaming infrastructure design.
Good knowledge and practical experience working in modern ELT/ETL environments, integrating diverse data sources into structured analytical stores.
Good knowledge and/or experience of software architecture design, lessons learnt and best practices in technologies used in projects worked in and current technology trends.
Good hands-on and grasping skills required for implementation of POCs and solutions in the technical space.
Knowledge of SAST, DAST, SCA and Grafana will be an added advantage.
Should have working knowledge on Agile Methodology.
Technical & Functional Skills
Python Programming: Advanced proficiency in writing production-ready Python code, adhering to clean architecture principles, building robust automation routines, and handling heavy data processing pipelines.
SQL & Database Management: Strong command over relational databases, query optimization, indexing strategies, and schema design.
Data Orchestration: Hands-on experience building, scheduling, and monitoring workflows using Apache Airflow.
Data Streaming & Messaging: Good understanding of event-driven architectures and real-time data pipelines using Kafka.
Infrastructure & Monitoring: Strong command over Linux environments, alongside familiarity with monitoring and logging tools like SIEM and Grafana.
Roles & Responsibilities
Design, build, and maintain scalable data pipelines and ETL workflows using Python and Apache Airflow.
Write, tune, and optimize complex SQL queries and data models across relational and search stores.
Integrate streaming data components using Kafka for real-time data ingestion.
Participate in Technical Discussions with Solution Architect and Managers.
Participate in Agile planning activities to understand the Processes and Requirements.
Understand Domain Model and Object Models.
Generic Skills
Strong communication skills
Strong analytical skills
Strong team skills
Benefits
Health Insurance
Mentoring (in a pure-play Data Science company)

Work arrangement
Yes