Senior Analytics Engineer

Dynatron Software, Inc.

Senior Analytics Engineer responsible for transforming raw data into actionable insights for an AI-enabled SaaS company. Leading data modeling and analytics engineering efforts while mentoring team members.

Posted 7/8/2026full-timeRemote • 🇮🇳 IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Expertise in transforming raw data into reliable models, with strong skills in SQL and Python for automation and tooling. Proficient in dbt for building version-controlled transformation pipelines and experienced in data governance and analytics operationalization using tools like Snowflake and Databricks.

Highest-signal resume keywords

SQL ExpertisePython ProficiencyDbt DevelopmentSnowflake ExperienceData Governance

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data ModelingData TransformationAutomated TestingData ProfilingPipeline Validation

Soft Skills

Documentation HabitsMentoring

Tools & Technologies

SnowflakeDatabricksDbtTableauPower BILookerKNIME

Certifications & Qualifications

Relevant IT Professional Certifications

Industry Keywords

Analytics EngineeringData AnalyticsData EngineeringBusiness IntelligenceGoverned Metrics

Tech Stack

Tools & technologies

AWSCloudPythonSQLTableau

About the role

Key responsibilities & impact

Responsible for transforming raw data into clean, reliable, and well-documented models that power analytics.
Design, build, and maintain transformation layers in dbt, following best practices for data modeling.
Own the semantic and metrics layer, defining governed, version-controlled business metrics.
Partner with BI developers to expose trusted datasets through BI tools.
Build and maintain documentation, data dictionaries, and lineage for stakeholders.
Own end-to-end data validation by building automated tests into the transformation workflow.
Collaborate on operationalizing analytics within services such as Snowflake Cortex and Databricks AI.
Mentor junior analysts and engineers in SQL and dbt best practices.

Requirements

What you’ll need

6-8+ years of experience in analytics engineering, data analytics, or data engineering with a focus on data modeling and transformation.
Demonstrated experience owning the complete development lifecycle, from requirements and design through testing, deployment, and production launch.
Very strong, expert-level SQL and Python skills for transformation, automation, and tooling.
Deep hands-on experience with dbt (Core or Cloud) building modular, tested, version-controlled transformation pipelines.
Deep hands-on experience with Snowflake or Databricks, ideally within an AWS ecosystem.
Proven track record delivering governed metrics and curated datasets to BI tools such as Tableau, Power BI, or Looker.
Bonus: Hands-on experience building and maintaining analytics model libraries across core business domains.
Experience working with data governance tools and platforms such as KNIME.
Demonstrated experience implementing automated testing frameworks, data profiling, and pipeline validation.
Strong documentation habits and an ownership mindset.
Relevant IT professional certifications are nice to have.

Benefits

Comp & perks

Remote-first environment offering flexibility, autonomy, and trust.
Opportunity to build and scale the data foundation of a growing, AI-enabled SaaS company.
High-impact role supporting real-time analytics, machine learning, enterprise reporting, and product innovation.
Close partnership across Data, Product, Engineering, Analytics, and business leadership.
Values-driven culture built on accountability, urgency, and delivering measurable results.