[Hiring] Senior Data Engineer @myKaarma

Role Description

As a Senior Data Engineer, you will build and run the engineering controls that make Mykaarma's reporting products, shared data models, and downstream feeds reliable, testable, traceable, and safe to change. You will translate the reporting platform's architectural direction into durable production mechanisms. You'll be accountable for automated testing, release safety, data quality, reconciliation, dependency visibility, and operational reliability across the transformation and semantic layers. You'll think in data products rather than isolated tables or dashboards, and you'll understand how grain, late-arriving data, slowly changing dimensions, cross-DMS variation, and join fan-out affect business correctness—not just query performance.

• Design and implement end-to-end automated testing for critical reporting outputs across dbt, LookML, and associated data products.
• Build CI/CD guardrails that prevent unsafe changes from reaching production, including environment separation, release checks, and rollback readiness.
• Define and operate data-quality controls: schema tests, variance monitoring, freshness checks, anomaly detection, and reconciliation to the DMS source-of-truth.
• Establish visibility into dependencies and lineage so teams can assess downstream impact before changing shared fields, models, or contracts.
• Implement agreed standards for V2 Explores, dbt models, semantic definitions, and reusable reporting components.
• Partner with upstream and downstream teams to implement data contracts, schema-change notification, contract tests, and delivery evidence for OEM feeds.
• Participate in and help mature the reporting on-call rotation; lead root-cause analysis, corrective actions, and repeat-incident reduction.
• Document engineering standards and automate their enforcement so quality does not depend on individual memory or manual review.
• Mentor engineers contributing to the reporting stack and review changes against documented specifications and operating standards.
• Implement technical controls that support the agreed data-governance model, including ownership metadata, lineage, quality rules, and controlled change workflows.

Qualifications

• Five or more years of relevant data-engineering or analytics-engineering experience in production; exceptional four-year candidates may qualify with equivalent end-to-end ownership.
• Advanced SQL and strong data-modeling fundamentals, including explicit grain, dimensional modeling, late-arriving facts, slowly changing dimensions, idempotency, and reconciliation.
• Production experience with dbt or an equivalent transformation framework, including tests, documentation, modular modeling, and CI/CD integration.
• Experience operating a cloud analytical warehouse; BigQuery is preferred, and comparable depth in Snowflake, Redshift, or Synapse is transferable.
• Experience with a semantic or BI modeling layer; LookML/Looker is preferred.
• Proficiency in Python or an equivalent language for data tooling, validation, and automation.
• Demonstrated ownership of data-quality, observability, incident response, and reliability outcomes—not only pipeline development.
• Experience with Git-based engineering workflows, code review, automated deployment, and production change controls.
• Ability to communicate tradeoffs clearly with product, engineering, analytics, and business stakeholders.

Requirements

• Experience implementing data-governance controls or operating models, such as ownership, lineage, cataloging, quality policies, access controls, or schema-change governance.
• Experience with multi-tenant SaaS reporting, shared semantic models, and customer-facing analytical SLAs.
• Hands-on work with data contracts, event-driven architectures, streaming systems, Kafka/Confluent, or Pub/Sub.
• Experience with cross-source canonical modeling, especially where upstream systems represent the same business entity differently.
• Experience supporting externally delivered data feeds, OEM/partner reporting, or regulated/auditable data products.
• History of mentoring engineers and scaling standards across multiple contributing teams.
• Experience with Java application development and the Spring Boot framework.

Benefits

• Flexible Work Environment: We embrace a high-performance, flexible structure that values freedom and responsibility. Our “Highly Aligned, Loosely Coupled” model empowers teams to innovate and continuously improve using data-driven insights.
• Health and Wellness: Comprehensive medical, dental, vision, life, and disability benefits, along with wellness and telework stipends.
• Time Off: Generous vacation time to recharge and balance life outside work.
• In-Office Perks: Enjoy dog-friendly offices and unlimited snacks or refreshments onsite.