Senior Data Engineer - Databricks

Intetics Inc. is a global technology company specializing in custom software development, AI-powered solutions, cloud technologies, and digital transformation. With over 30 years of experience, we help organizations worldwide build scalable, innovative, and data-driven solutions across a wide range of industries. We are looking for talented professionals who are passionate about solving complex technical challenges and building high-quality data platforms.
Impact You Will Make in the Role:

- Own Databricks production support for the company's data platform, including monitoring, alerting, and incident response across all production data flows.

- Maintain and report on SLA performance metrics for data pipeline delivery, ensuring visibility into platform health and accountability across internal and external stakeholders.

- Identify and implement pipeline optimizations that reduce Databricks compute costs, improve throughput, and reduce processing windows while tracking impacts through measurable KPIs.

- Migrate legacy ETL/ELT pipelines to Databricks, building automation tooling to reduce manual intervention and ensure uninterrupted data delivery during transitions.

- Support new customer onboarding by provisioning, validating, and hardening tenant data pipelines that deliver reliable, isolated data from day one.

- Design and build high-performance Databricks pipelines that ingest, transform, and serve ERP and CRM data at scale across both Azure and AWS environments.

- Own the Delta Lake architecture, including schema design, partitioning strategies, data quality enforcement, and incremental processing patterns.

- Enforce data security best practices across Databricks environments, including role-based access control, secrets management, and compliance requirements for enterprise business data.

- Implement data quality monitoring and observability across pipeline health and ML model inputs, ensuring data integrity that directly supports predictive analytics.

- Apply and enforce multi-tenant data isolation patterns, ensuring reliable and secure data delivery across enterprise customers.

- Partner with the Enterprise Architecture team to ensure data pipelines integrate seamlessly with the broader AI and analytics ecosystem.

- Support a globally distributed operation through on-call rotation and after-hours incident response, meeting SLAs across multiple time zones.

- Maintain technical documentation, runbooks, and architectural decision records, contributing to team knowledge sharing and operational readiness across on-call and incident response scenarios.

- Apply CI/CD best practices to data pipeline development, including version control, automated testing, and deployment tooling to ensure reliable and repeatable pipeline delivery.

Requirements
What You Will Bring:

- 4+ years of data engineering experience.

- At least 2 years of experience with Databricks or the Apache Spark ecosystem across Azure and/or AWS.

- Proficiency in PySpark, SQL, and Python with a strong track record of building and operating production-grade pipelines under SLA constraints.

- Hands-on experience with Delta Lake, including schema evolution, ACID transactions, optimize/vacuum lifecycle, and both incremental and streaming processing patterns.

- Hands-on experience with pipeline performance tuning and compute optimization in production Databricks environments.

- Solid working knowledge of PostgreSQL, including query optimization, schema design, and use as a source or sink in production data pipelines.

- Experience supporting and maintaining legacy ETL tooling (SSIS, Informatica, custom Python/SQL pipelines, or similar) in production.

- Experience supporting large-scale multi-tenant architectures with a focus on tenant isolation, per-tenant performance, and data privacy, including navigating tools and platforms that default to single-tenant assumptions.

- Proven ability to work collaboratively across data s