Senior Software Engineer - Data Engineering

ITRADENETWORK LEADERSHIP PRINCIPLES

iTradeNetwork’s purpose is to feed the world — and everything we do is guided by the principles below. Every team member is expected to embody and champion these principles across the organization.

Bias for Action

We value speed and avoid analysis paralysis. We develop conviction, make informed decisions quickly, and take calculated risks to maintain momentum — knowing that swift progress is essential for innovation and growth.

Customer Obsession

We work relentlessly to delight our customers. We work backward from their needs to solve pain points and create solutions that surprise and earn their loyalty. We obsess over customers, not competitors.

Data & Metrics Driven

We operate with facts, not opinions. We dive deep into data and use metrics to measure progress, ground every decision in rigorous analysis, and push for clarity and measurable outcomes.

Raise the Bar

We continuously push for improvement — in ourselves, our teams, and the company. We hire and develop exceptional talent, setting ever-higher standards that elevate performance and drive excellence.

Operational Excellence Through Process

We build lasting processes that optimize for efficiency. By developing, testing, and documenting each process, we create consistency and scale through automation, enabling continuous improvement across the business.

Ownership Mindset

We take responsibility for our work and aim for long-term success. We use resources wisely, stay accountable, and roll up our sleeves to get things done — no task is beneath us.

Earn Trust

We build trust through integrity, transparency, and mutual respect. We communicate openly, own our mistakes, listen actively, and remain open to feedback as an opportunity for growth.

JOB SUMMARY

We are seeking an experienced and strategic Senior Software Engineer - Data Engineering to lead the design, development, and optimization of our enterprise-scale data infrastructure. In this role, you will architect and champion highly scalable, secure, and cost-effective data systems that power analytics, reporting, ML, and data products across the organization. This role combines hands-on technical leadership, cross-functional influence, platform ownership, and mentorship of engineering teams. You’ll be a core contributor to our long-term data strategy, execution, and operational excellence.

As a Staff Data Engineer, you will work closely with engineering leadership, data scientists, analysts, product managers, and stakeholders to translate business needs into robust, production-grade data solutions.

• Platform & Strategy Impact: You won’t just write pipelines — you’ll define how data is built, shared, governed, and evolved across the company.
• Leadership Beyond Code: Influence engineering standards, technology choices, and business outcomes.
• Cross-Team Visibility: Work with diverse teams from analytics to product to executive leadership.
• Ownership & Autonomy: Champion initiatives from architectural plans through deployment and live operations.

Key Responsibilities:

Architect & Build

• Lead the architecture, design, and implementation of scalable data platforms (data lakes, warehouses, streaming, OLAP/OLTP stores).
• Define and own end-to-end data pipeline frameworks for real-time and batch data ingestion, processing, transformation, and serving.
• Establish reusable frameworks and abstraction layers that increase development velocity and reduce operational risk.

Technical Leadership & Strategy

• Drive long-term strategy for data infrastructure, tooling, and processes aligned with business goals.
• Act as technical authority and point of escalation for complex data engineering challenges.
• Set standards for engineering excellence (code quality, architecture, performance, security, observability, and cost-efficiency).

Cross-Functional Collaboration

• Partner with product and business teams to understand analytic and operational requirements and translate them into deliverables.
• Collaborate with data scientists and ML engineers to productionize models and analytics.
• Influence cross-team prioritization and roadmap decisions through technical insight and business impact.

Platform Reliability & Operations

• Build and enforce robust practices for monitoring, alerting, quality, change management, and incident response.
• Ensure data accuracy, reliability, lineage, and compliance across data workflows.
• Lead architectural capacity planning, performance tuning, and cost optimization initiatives.

Mentorship & Team Development

• Coach and mentor senior and mid-level data engineers; provide technical reviews and guidance.
• Help build a strong engineering culture focused on collaboration, learning, and high-quality delivery.

What you’ll need:

• 10+ years of professional experience in data engineering, software engineering, or related fields.
• Proven experience architecting large-scale data platforms used for analytics, operational reporting, and ML/AI.
• Deep expertise in designing and building scalable ETL/ELT pipelines, data warehouses, and data lakes.
• Strong background in distributed data processing (e.g., Spark, Flink, Hadoop) and realtime systems (e.g., Kafka, Kinesis).
• Demonstrated success owning engineering workstreams end-to-end (design → deployment → operational support).

Technical Skills

• Advanced proficiency in SQL and at least one programming language (Python, Java, Scala).
• Experience with cloud data platforms and infrastructure (AWS preferred: Redshift, S3, Glue, Lambda, EMR, Athena, Kinesis).
• Data modeling expertise (dimensional, star/snowflake schemas, OLAP design).
• Strong understanding of data governance, quality frameworks, and metadata practices.
• Hands-on experience with orchestration tools (e.g., Airflow, dbt, or similar).

Leadership & Communication

• Exceptional problem-solving, analytical, and strategic thinking skills.
• Excellent written and verbal communication; capable of translating complex concepts for technical and non-technical audiences.
• Track record of influencing technical direction and collaborating with senior leadership.

 

Nice-to-Have Qualifications:

• Master’s degree or higher in Computer Science, Engineering, Mathematics, or related field.
• Experience in highly regulated or consumer-facing environments with strong security and compliance needs.
• Prior experience mentoring across teams and shaping engineering culture.
• Familiarity with containerization, CI/CD, IaC (Terraform/CloudFormation), and observability tools.

 

If you are a highly motivated and results-driven individual, with a passion for driving growth in a fast-paced, entrepreneurial environment,  we encourage you to apply for this exciting opportunity. We offer a competitive salary, comprehensive benefits package, and a dynamic work culture that values collaboration, innovation, and personal development.

 

Base Compensation:  $166,000 - $172,000 per year