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Sr. Data Engineer-Azure, Snowflake, Python, SaaS
Streamline
- United States
- United States
Über
Sr. Data Engineer In our flagship product, iEnterprise, we are taking things to the next level, using our collective experience and customer input to create new enterprise mobility management products that reduce operational costs, prevent issues before they happen, and resolve issues faster than with traditional tools and approaches.
Role Summary This is a full‑time remote opportunity. The Senior Data Engineer designs, builds, and optimizes data pipelines that move, transform, and load data into Snowflake using Azure services and serverless components. The role focuses on production‑grade engineering: automating data quality, improving reliability, and continuing to optimize cloud infrastructure costs.
Role Responsibilities
Design, develop, and deploy Azure Functions and broader Azure data services to extract, transform, and load data into Snowflake data models and marts
Implement automated data quality checks, monitoring, and alerting to ensure accuracy, completeness, and timeliness across all pipelines
Optimize workloads to reduce cloud hosting costs, including right‑sizing compute, tuning queries, and leveraging efficient storage and caching patterns
Build and maintain ELT/ETL workflows and orchestration to integrate multiple internal and external data sources at scale
Design data pipelines that support both near real‑time streaming data ingestion and scheduled batch processing to meet diverse business requirements
Collaborate with engineering and product teams to translate requirements into robust, secure, and highly available data solutions
Qualifications & Skills
Strong expertise with Azure data stack (e.g., Azure Functions, Azure Data Factory, Event/Service Bus, storage) and Snowflake for analytical workloads
Proven experience designing and operating production data pipelines, including CI/CD, observability, and incident response for data systems
Advanced SQL and performance tuning skills, with experience optimizing transformations and Snowflake queries for cost and speed
Solid programming experience in Python or similar for building reusable ETL components, libraries, and automation
Experience with streaming and batch ingestion patterns (e.g., Kafka, Spark, Databricks) feeding Snowflake
Familiarity with BI and analytics tools (e.g., Power BI, Grafana) consuming Snowflake data models
Background in DevOps practices, including containerization, CI/CD pipelines, and infrastructure‑as‑code for data platforms
Experience with modern data transformation tools (e.g., dbt) and data observability platforms for monitoring data quality, lineage, and pipeline health
Additional Requirements
Ability to adapt to a fast‑paced and dynamic work environment
Self‑motivated and able to work independently with minimal supervision, taking initiative to drive projects forward
Expert‑level problem‑solving skills with the ability to diagnose complex data pipeline issues and architect innovative solutions
Proven ability to integrate and analyze disparate datasets from multiple sources to deliver high‑value insights and drive business impact
Strong problem‑solving skills and attention to detail
Proven ability to manage multiple priorities and deadlines
Passionate about staying current with emerging data engineering technologies and best practices, driving innovation to enhance product capabilities and maintain competitive advantage
Experience developing and architecting SaaS platforms with a focus on scalability, multi‑tenancy, and cloud‑native design patterns
What We Offer
A challenging and rewarding role in a dynamic and international environment
Opportunity to be part of a growing company with a strong commitment to innovation and excellence
A supportive and collaborative team culture that values personal growth and development
Competitive compensation and benefits package
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Sprachkenntnisse
- English
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