We’re hunting for a Data Engineer who loves big data, fast streams, and clever solutions. In our AdTech playground, you’ll design lightning-fast pipelines, tame massive datasets, and fuel smarter ad decisions for global brands.

Think real-time bidding, machine-learning models, and Millions of events a day—if that sounds like your kind of challenge, let’s talk.

Responsibilities

• Design, develop, maintain, and own data engineering projects based on requirements from product, BI, data science, and analytics teams.
• Fulfill requirements related to data pipelines, warehouses, and databases.
• Handle high-volume data ingestion using APIs, scrapers, parsers, and similar tools.
• Create and optimize ingestion pipelines to collect and deliver data from multiple sources to targets.
• Perform data cleaning and transformation on very large datasets.
• Design and create SQL objects: tables, procedures, functions, and views.
• Operate and maintain clusters and supporting infrastructure.
• Evaluate, test, and update data applications as requirements evolve.
• Monitor and report on data systems’ health, performance, and security.
• Support internal teams, troubleshoot issues, and resolve them.
• Follow best coding practices, participate in code reviews, and use CI/CD and version control tools efficiently.

Technical Competencies

Must Have

• 3–5 years of experience in Data Engineering.
• Python proficiency (mandatory).
• Knowledge of data cleaning and data transformation on large datasets.
• Knowledge of hardware resource management while handling large datasets (preferred but critical for performance).
• Experience with Airflow for workflow orchestration.
• Hands-on experience with SQL (queries, stored procedures, and database code).
• Understanding of ETL/ELT processes, data lakes, and warehouses.
• Experience with relational databases (MySQL, PostgreSQL, MariaDB).
• Familiarity with Git, CI/CD pipelines, and writing unit tests.
• Comfortable working in agile environments using Jira/Atlassian.

Preferred / Nice to Have

• Knowledge of Hadoop, Spark, and Kafka.
• Knowledge of equivalent technologies on AWS, GCP, or Azure.
• Knowledge of Chalice framework.
• Knowledge of Greenplum.
• Knowledge of AI/ML techniques for user profiling and classification.
• Experience with NoSQL databases (Aerospike, DynamoDB, Redis, Elasticsearch, Cassandra, MongoDB).
• Knowledge of Snowflake (schemas, stages, pipes, tasks, procedures, views).
• Experience with performance tuning, scalability issues, and hardware optimization.
• Familiarity with ETL tools beyond Airflow.
• Linux shell scripting knowledge.

Non-Technical Competencies

• Strong English communication skills.
• Positive, proactive, and collaborative attitude.
• Ability to work independently and in a team.
• Problem-solving mindset with innovative thinking.
• Self-starter and contributor who thrives on challenges.

What we offer

• Competitive Salaries in USD 
• Family Medical insurance
• Hybrid mode