Senior Data Engineer

What if you could build software that didn't just scale, but transformed entire organizations? At Tactable, this is what drives us. We’re building a world-class cloud, data, and API engineering firm with a mission to power the most influential tech of tomorrow, through expert-led delivery, strong partnerships, and a relentless focus on quality.

Founded by engineers who care deeply about people, process, and product, we go beyond just solving problems. We embed with clients, work across full project lifecycles, and operate at the speed of startups while upholding the rigor of enterprise-grade engineering.

From financial institutions to emerging tech ventures, our work is behind some of the most mission-critical systems in production today, and we’re just getting started. With growing demand from top-tier clients and a strong runway for expansion, we’re building a team of curious, ambitious developers who want to build meaningful things with meaningful people.

Take a look at tactable.io to learn more about our work and what sets us apart.

The Role: Senior Data Engineer (Cloud, Python) This is a hands-on, hybrid role designed for data engineers who thrive at the intersection of infrastructure, pipelines, and product. As a

Senior Data Engineer , you’ll be part of a deeply technical team solving real-world data challenges for enterprise clients building robust, cloud-native data platforms, optimizing large-scale workflows, and delivering reliable data systems in production environments.

You’ll have the opportunity to own architectural decisions, drive platform migrations, and mentor others across data and software engineering domains. Whether you're scaling a trading system or modernizing a legacy data warehouse, your work will be high-impact and highly visible.

If you care about clean pipelines, scalable architecture, and building systems that power real users, you’ll thrive at Tactable.

What You'll Do End-to-End Data Engineering

Build scalable, reliable

ETL/ELT pipelines

using

Python , and

SQL

Design and maintain batch and near-real-time data workflows using Python-based frameworks

Integrate diverse data sources from

Azure Blob ,

ADLS , and both relational and non-relational systems

Migrate legacy data architectures into modern, cloud-native environments

Optimize workloads for performance, cost, and fault tolerance

Ensure data quality, observability, and reliability across pipelines

Technical Leadership

Own critical components of infrastructure across batch and streaming systems

Break down complex technical challenges into executable components

Mentor junior engineers through code reviews, architectural guidance, and technical pairing

Automate and standardize pipelines to reduce overhead and increase velocity

Contribute to internal tooling, documentation, and engineering best practices

Client & Project Exposure

Work directly with client engineering teams in finance, trading, and enterprise tech

Rotate across domains and industries every 6-12 months, gaining broad exposure to systems and technologies

Tackle greenfield builds, system migrations, and enterprise-scale data transformations

Engage as a true partner, not a vendor, in shaping data product strategy

What You Bring Must-Have Experience

8+

years of extensive experience in

data engineering or software engineering

roles

Strong programming skills in

Python

Deep experience building and maintaining

production-grade data pipelines

Strong

SQL

skills and experience working with both structured and unstructured data

Hands‑on experience with

cloud infrastructure

(preferably Azure)

Experience with

CI/CD pipelines

and infrastructure-as-code practices

Familiarity with

data orchestration tools

(e.g., Airflow, dbt)

Experience working in

containerized environments

(Docker, Kubernetes)

Bonus Points For

Experience working in finance, trading, or other regulated / high-performance environments

Experience with Databricks or similar managed data platforms

Strong documentation, collaboration, and knowledge-sharing mindset

Comfort working across the full data lifecycle, from ingestion to analytics and reporting

Why You'll Love This Role

Growth-First Culture:

From custom career paths to project rotation, we design roles around your goals, not just business needs.

Full Ownership & Impact:

You’ll own critical parts of delivery, architecture, and technical decision-making. No red tape, no silos.

Tight-Knit Team:

We’ve built a culture of trust, collaboration, and curiosity. Whether it’s team lunches, hack days, or a new internal tool, we move as one unit.

Real Work, Real Users:

We’re not building MVPs that sit on a shelf. You’ll work on systems that millions rely on, every day.

Flexibility with Structure:

We’re a hybrid-first team with a strong appreciation for in-office collaboration, especially at our downtown Toronto HQ. We encourage in-person presence to foster mentorship, connection, and collaboration.

Why This Might Not Be a Fit

You’re looking for narrowly scoped responsibilities or long-term focus on a single domain

You prefer a rigid hierarchy with formal titles and isolated workstreams

You’re more comfortable in a vendor-style delivery model than deep technical partnerships

Salary Range: $140,000 - $190,000 CAD, based on experience and role fit

Comprehensive health and dental plan

Generous PTO and holidays

Laptop & home office equipment provided

Career coaching and personalized development plans

Regular social events, team outings, and wellness activities

Hiring Process & Transparency

This role is for an active vacancy on our engineering team, not a future talent pool position.

As part of our hiring process, we use AI-assisted screening tools. Candidates who move forward complete an initial screening interview via an AI-based platform, with results reviewed by Human Resources. Selected candidates then proceed to interviews with our engineering team.

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