Design, build, and maintain robust ETL/ELT pipelines that move data from diverse source systems into analytics, AI, and machine learning platforms.
Develop and optimize data architectures that support real-time and batch analytics, ML workflows, and personalization.
Partner with data architects, analysts, and client stakeholders to translate business requirements into technical designs.
Ensure data quality, lineage, observability, and security through validation, monitoring, and governance best practices.
Optimize performance and cost-efficiency of pipelines and storage.
Support cloud-first architectures across AWS, Azure, and GCP.

3–4+ years of experience in building production-grade data pipelines and data systems.
Strong proficiency in SQL, Python, or Java/Scala.
Experience with modern data platforms (Snowflake, BigQuery, Redshift, Databricks, Synapse).
Hands-on skills with streaming technologies (Kafka, Kinesis, Pub/Sub).
Knowledge of data modeling principles and schema design for analytics and operational systems.
Familiarity with DevOps and CI/CD practices for data, including version control (GitHub/GitLab), testing, and deployment automation.
Exposure to data governance, security, compliance, and observability frameworks.
Ability to collaborate in a consulting/client-facing environment, balancing technical depth with pragmatic delivery.

Generous paid company holidays, vacation, and paid sick time to every employee starting on day one.
Top-of-the-line Health Insurance, plus monthly perks customized to meet individual employees’ needs.
Support a healthy work/life balance.
Remote work options available for certain roles.

Data Engineer

Key skills