Sr Data Engineer

Instrumentl; United States; On-site; USD 120,000 - 160,000; Full time

Job summary

Instrumentl is seeking a Senior Data Engineer to enhance its data platform. The role entails designing and scaling data pipelines and implementing systems for data ingestion, processing, and storage. Ideal candidates will have robust experience in software engineering, specifically in data engineering within early-stage environments.

Key responsibilities include optimizing systems for performance and scalability while applying best practices in software engineering. Proficiency in Python, SQL, and ETL/ELT pipelines is essential.

Qualifications

• 5+ years of software engineering experience, with 2-3 years in data engineering.
• Proven experience building ETL/ELT pipelines end-to-end.
• Deep understanding of the data lifecycle from ingestion to serving.

Responsibilities

• Design and scale our data platform including pipelines and models.
• Develop scalable ETL/ELT pipelines for data ingestion.
• Define and implement systems for data storage and processing.

Skills

Python

SQL

ETL/ELT Pipeline Construction

Data Modeling

Workflow Orchestration

Tools

Airflow

AWS

GCP

Azure

Looker

Tableau

Snowflake

BigQuery

Redshift

Kafka

Kinesis

Job description

Senior Data Engineer

We’re looking for a Senior Data Engineer to help scale and evolve our data platform, which is in its early stages. You’ll play a key role in shaping the architecture, improving reliability, and building the systems that power data across the company. This is a high-impact opportunity to bring structure and scalability to an existing foundation—ideal for someone who enjoys improving systems, making architectural decisions, and driving best practices.

Responsibilities

• Design and scale our data platform including pipelines, models, and orchestration frameworks
• Develop scalable ETL/ELT pipelines for ingesting data from APIs, databases, and event streams
• Define and implement systems for data ingestion, storage, processing, and transformation
• Build and manage workflow orchestration using tools like Airflow
• Build semantic layer as well as dashboards
• Establish best practices for data modeling, testing, and quality
• Partner with stakeholders to shape data requirements and enable BI and analytics use cases
• Optimize systems for performance, scalability, and cost from day one
• Apply software engineering principles (testing, CI/CD, modular design) to data infrastructure

Qualifications

• A minimum of 5+ years of software engineering experience with the last 2-3 years in data engineering, ideally including early-stage or 0 to 1 environments
• Strong Python programming experience
• Advanced proficiency in SQL
• Proven experience building ETL/ELT pipelines end-to-end
• Experience with orchestration tools like Airflow
• Deep understanding of the data lifecycle: ingestion to storage to processing to transformation to serving
• Experience with cloud platforms (AWS, GCP, or Azure)
• Experience supporting BI tools (Looker, Tableau, etc.)
• Familiarity with modern data warehouses (Snowflake, BigQuery, Redshift)

Nice to have

• Experience with streaming pipelines (Kafka, Kinesis)
• Exposure to ML/AI data pipelines
• Familiarity with Ruby and Rails
• Experience with data analytics and data science concepts
• Experience working in startup environments