Build and maintain reliable, scalable ETL/ELT pipelines using modern tools and best practices, ensuring efficient data flow for analytics and insights.
Design and implement effective data models that support business needs, enabling high-quality reporting and downstream analytics.
Work closely with data analysts, product managers, and other engineers to understand data requirements and deliver solutions that meet the needs of the business.
Develop and apply data quality checks, validation frameworks, and monitoring to ensure the consistency, accuracy, and reliability of data.
Identify and address performance issues in pipelines, queries, and data storage. Suggest and implement optimizations that enhance speed and reliability.
Follow data security best practices and ensure pipelines are built to meet data privacy and compliance standards.
Test new tools and approaches by building Proof of Concepts (PoCs) and conducting performance benchmarks to find the best solutions.
Contribute to the development of robust CI/CD pipelines (GitLab CI or similar) for data workflows, supporting automated testing and deployment.

4+ years of experience in data engineering or backend development, with a strong focus on building production-grade data pipelines.
2-3+ years of experience working with AWS services (Administration of Redshift is a must)
Solid experience working with AWS services (Spectrum, S3, RDS, Glue, Lambda, Kinesis, SQS).
Proficient in Python and SQL for data transformation and automation.
Experience with dbt for data modeling and transformation.
Good understanding of streaming architectures and micro-batching for real-time data needs.
Experience with CI/CD pipelines for data workflows (preferably GitLab CI).
Familiarity with event schema validation tools/ solutions (Snowplow, Schema Registry).
Excellent communication and collaboration skills.
Strong problem-solving skills—able to dig into data issues, propose solutions, and deliver clean, reliable outcomes.
A growth mindset—enthusiastic about learning new tools, sharing knowledge, and improving team practices.

Experience with additional AWS services: EMR, EKS, Athena, EC2.
Hands-on knowledge of alternative data warehouses like Snowflake or others.
Experience with PySpark for big data processing.
Familiarity with event data collection tools (Snowplow, Rudderstack, etc.).
Interest in or exposure to customer data platforms (CDPs) and real-time data workflows.

Grow Together: Join a culture that champions both personal and professional growth.
Lead by Example: Every team member is empowered to inspire and make an impact.
Results-Driven: Focus on achieving meaningful outcomes.
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Welltech is hiring a Senior Data Engineer (Redshift)