Data Engineer

Role Summary We are looking for a Data Engineer with 3–6 years of experience who thrives on solving complex data problems, building scalable data systems, and enabling high-quality analytics across the organization. This role will play a critical part in onboarding newly acquired brands, integrating diverse data ecosystems, and building reliable, scalable data infrastructure that powers decision-making across business, product, and operations. Key Responsibilities Design, build, and maintain scalable data pipelines and ETL/ELT workflows for batch and near real-time processing Develop and optimize data models, schemas, and warehouse structures for analytics, reporting, and downstream applications Build robust data ingestion frameworks integrating multiple sources including databases, APIs, SaaS tools, and third-party platforms Implement data transformation, validation, and quality checks for partially structured and unstructured datasets Perform root-cause analysis on data issues , ensuring reliability, accuracy, and observability of pipelines Build and manage data infrastructure on cloud platforms , optimizing performance and cost Collaborate closely with product managers, analysts, data scientists, and engineering teams to deliver business-ready datasets Enable secure data access, governance, and documentation across systems Contribute to standardized onboarding and migration frameworks for integrating newly acquired brands into Mensa’s data platfor Required Skills & Qualifications Bachelor’s degree in Computer Science, Engineering, or related field 3–6 years of hands-on experience in data engineering or backend data systems Strong proficiency in SQL and relational databases (PostgreSQL, MySQL, etc.) Strong programming skills in Python (preferred), with exposure to Java or Scala Hands-on experience building ETL/ELT pipelines and data transformation frameworks Experience with cloud data platforms and warehousing such as Amazon Redshift, BigQuery, or Snowflake Practical experience with AWS ecosystem , especially: AWS Glue / Glue Jobs Amazon S3 Redshift Lambda / Step Functions (nice to have) Experience working with big data processing frameworks such as Apache Spark Strong understanding of data modeling, partitioning, indexing, and performance tuning Familiarity with Git-based version control and CI/CD workflow Strong analytical mindset with attention to data accuracy, structure, and scalability Good to Have Experience with workflow orchestration tools like Airflow, Dagster, or Prefect Exposure to streaming and real-time data systems such as Kafka, Kinesis, or Pub/Sub Familiarity with data lake architectures and lakehouse patterns Understanding of analytics, BI, or machine learning data requirement Experience working in a startup, high-growth, or acquisition-driven environment