Adsremedy Media LLP

About the Role:

We are seeking a skilled Data Engineer to join our growing AdTech team. In this role, you will design, build, and maintain high-performance ETL pipelines and large-scale data processing systems. You will work with massive datasets and distributed frameworks to power Adsremedy’s data-driven advertising solutions across Programmatic, In-App, CTV, and DOOH platforms.

What You’ll Do:

• Design, develop, and maintain scalable ETL pipelines on self-managed infrastructure
• Process and optimize large-scale datasets (terabytes of data) with high reliability and performance
• Build robust data processing workflows using Apache Spark (preferred) and/or Apache Flink
• Integrate, clean, and transform data from multiple internal and external sources
• Partner closely with data scientists, analysts, and business stakeholders to enable actionable insights
• Monitor, troubleshoot, and optimize data pipelines for operational excellence
• Ensure data quality, consistency, and performance across all data workflows
• Participate in code reviews and uphold best practices in data engineering
• Collaborate with QA teams to deliver production-ready, reliable systems
• Mentor junior engineers and promote knowledge sharing within the team
• Stay current with emerging data engineering tools, frameworks, and industry trends

What You’ll Need:

• 2+ years of experience building ETL pipelines using Apache Spark and/or Apache Flink
• Hands-on experience with big data caching solutions such as ScyllaDB, Aerospike, or similar
• Strong understanding of data lake architectures and tools like Delta Lake
• Proven experience handling terabytes of data in distributed environments
• Proficiency in Scala, Python, or Java
• Experience working with cloud data platforms (AWS S3, Azure Data Lake, Google BigQuery)
• Strong knowledge of SQL, data modeling, and data warehousing concepts
• Familiarity with Git and CI/CD workflows
• Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment

Nice to Have

• Experience with Apache Kafka for real-time data streaming
• Familiarity with Apache Airflow or similar orchestration tools

What You’ll Do:

● Lead and mentor a team of backend engineers, providing technical direction, guidance, and

performance feedback

● Architect, design, and develop scalable backend services and APIs using Golang

● Own SQL database design, optimization, indexing, and performance tuning to ensure data integrity

and efficiency

● Work closely with Product, QA, DevOps, and Analytics teams to translate business requirements

into robust technical solutions

● Drive best practices in system design, code quality, security, and reliability

● Troubleshoot and resolve complex issues across development, staging, and production

environments

● Oversee CI/CD pipelines and ensure smooth, reliable deployments

● Conduct and participate in code reviews to maintain high engineering standards

● Collaborate with QA teams to ensure thorough testing and high-quality releases

● Stay updated with emerging technologies and industry trends, recommending and implementing

improvements where applicable

● Foster a collaborative, innovative, and growth-oriented engineering culture

What You’ll Need

● 6+ years of professional software engineering experience, including 3+ years of hands-on Golang

development

● Proven experience leading or managing engineering teams

● Strong expertise in SQL databases (schema design, query optimization, indexing, performance

tuning)

● Hands-on experience with Columnar OLAP databases (Druid, ClickHouse, or similar)

● Hands-on experience with OLTP databases (ScyllaDB, Redis, or similar)

● Solid understanding of microservices architecture, RESTful APIs, and distributed systems

● Experience with Docker, Kubernetes, and cloud platforms (AWS / GCP / Azure)

● Strong proficiency with Git and collaborative development workflows

● Deep understanding of concurrency, performance optimization, and memory management in

Golang

Nice to Have:

● Experience with NoSQL databases and data modeling

● Exposure to messaging systems such as Kafka, RabbitMQ, or similar

● Familiarity with monitoring and observability tools (Prometheus, Grafana, ELK stack)

● Experience working in Agile / Scrum environments