Senior Data Engineer

About Pocket FM

Pocket FM is a leading audio entertainment platform focused on immersive, long-form audio storytelling. The platform offers episodic audio series across genres such as romance, drama, thriller, and fantasy. Pocket FM follows a mobile-first approach, enabling users to listen anytime and anywhere. Founded in India, the company has expanded rapidly across global markets, including the US.It supports multiple regional and international languages to reach a diverse audience. Pocket FM empowers creators through a strong content and monetization ecosystem

About the Role

We are seeking a talented AI & Data Engineer to join our team. In this role, you will design, build, and maintain robust data pipelines while developing and deploying cutting-edge AI solutions. You will work at the intersection of data engineering and artificial intelligence, leveraging modern cloud platforms and AI frameworks to drive business value.

We are seeking a skilled Data Engineer to join our team. The candidate will be responsible for designing, building, and maintaining robust data infrastructure that powers PocketFM's recommendation systems, analytics, and business intelligence capabilities. This role offers an exciting opportunity to work with large-scale data systems that directly impact millions of users audio entertainment experience.

Key Responsibilities:

Data Infrastructure & Pipeline Development

Design, develop, and maintain scalable ETL/ELT pipelines to process large volumes of user interaction data, content metadata, and streaming analytics

Build and optimize data warehouses and data lakes to support both real-time and batch processing requirements

Implement data quality monitoring and validation frameworks to ensure data accuracy and reliability

Develop automated data ingestion systems from various sources, including mobile apps, web platforms, and third-party integrations

Analytics & Reporting Infrastructure

Create and maintain data models that support business intelligence, user analytics, and content performance metrics

Build self-service analytics platforms enabling stakeholders to access insights independently

Implement real-time dashboards and alerting systems for key business metrics

Support A/B testing frameworks and experimental data analysis requirements

Data Architecture & Optimization

Collaborate with software engineers to optimize database performance and query efficiency

Design data storage solutions that balance cost, performance, and accessibility requirements

Implement data governance practices including data cataloging, lineage tracking, and access controls

Ensure GDPR and data privacy compliance across all data systems

Collaboration & Support

Work closely with data scientists, product managers, and analysts to understand data requirements

Participate in code reviews and maintain high standards of code quality and documentation

Mentor junior team members and contribute to knowledge-sharing initiatives

Required Qualifications

Technical Skills

Programming Languages: Proficiency in Python, SQL

Big Data Technologies: Hands-on experience with Apache Spark, Kafka, Airflow, and distributed computing frameworks

Cloud Platforms: Strong experience with AWS(S3, EMR etc.)

Database Systems: Expertise in both SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra, Redis) databases

Data Warehousing: Experience with modern data warehouse solutions like Databricks, Snowflake or BigQuery

Containerization: Proficiency with Docker and Kubernetes for deploying data applications

Experience Requirements

4 years of experience in data engineering or related roles

Proven track record of building and maintaining production data pipelines at scale

Experience with streaming data processing and real-time analytics systems

Strong understanding of data modeling, schema design, and data architecture principles

Experience with version control systems (Git) and CI/CD pipelines

Advanced Technical Skills

Understanding of data mesh architecture and domain-driven data design

Experience with data privacy and security implementations

Agentic-AI automation approach for Data and Analytics