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Miratech

Senior Data Architect

Toronto, ON, Canada
Scarborough, ON, Canada

Full-time

Apply About employer

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Job details

Job type: Full-time
Apply by: May 5, 2027
Experience: 5+ years of hands-on experience with Databricks/Delta Lake and Snowflake or API-driven ingestion.
Posting language: English
Posted: Nov 6, 2026

Original job description

Miratech helps visionaries change the world. We are a global IT services and consulting company that brings together enterprise and start-up innovation. Today, we support digital transformation for some of the world's largest enterprises. By partnering with both large and small players, we stay at the leading edge of technology, remain nimble even as a global leader, and create technology that helps our clients further enhance their business. We are a values-driven organization and our culture of Relentless Performance has enabled over 99% of Miratech's engagements to succeed by meeting or exceeding our scope, schedule, and/or budget objectives since our inception in 1989.

Miratech has coverage across 5 continents and operates in over 25 countries around the world. Miratech retains nearly 1000 full-time professionals, and our annual growth rate exceeds 25%.

Job Description

We are looking for a Senior Data Architect to design the end-to-end data platform for APEX. The platform ingests contact centre telephony and quality data from the Genesys A3S Snowflake database and Verint Workforce Management (WFM) feeds, and delivers it through a Bronze/Silver/Gold (Medallion) architecture on Databricks into a Kimball-style reporting layer.

You will own the architecture: ingestion strategy and cadence per source, incremental loading and batch control, data integrity standards, and the Gold-layer dimensional model. You will also partner with the existing CCARS pipeline team through parallel run and decommissioning of the legacy pipelines.

This role suits a hands-on Senior or Lead Data Architect who can turn complex reporting requirements into robust, auditable data solutions and explain architectural trade-offs to both engineers and business stakeholders.

Working Model: This is a hybrid role requiring 2 days per week in a downtown Toronto office.

Responsibilities:

Design the Bronze/Silver/Gold data flow for the new Genesys A3S Snowflake and Verint sources, with clear standards for ingestion, transformation, validation, and consumption.
Experience with contact center migrations; Genesys Cloud experience is a big plus.
Define ingestion cadence and watermarking strategy per source, based on each source's true data freshness.
Design the Gold-layer Kimball star schema (facts, dimensions, grain, SCD Type I/II) to support sales, telephony, agent activity, and quality reporting.
Choose between pure lakehouse and hybrid lakehouse-to-data-warehouse patterns based on source characteristics, volumes and performance needs.
Build and optimize Databricks and Delta Lake pipelines, and set cost and performance practices for cluster sizing, job versus all-purpose compute, and Photon.
Design ingestion from the external Genesys Snowflake source, including secure connectivity, incremental extraction and source-to-target reconciliation.
Integrate Verint and other vendor feeds delivered as flat files, SFTP drops or REST APIs, normalizing inconsistent formats and tolerating schema drift.
Design API ingestion that handles pagination, rate limits, asynchronous submit-poll-retrieve jobs and per-entity fan-out at scale.
Define data integrity checks, batch control, idempotency and failure-recovery patterns for each pipeline, including row-count and checksum reconciliation and late-arriving data handling.
Design orchestration with Azure Data Factory, Databricks Workflows or equivalent, with independent batch tracking and failure isolation per source feed.
Write and review production-grade transformation logic in T-SQL, Spark SQL and Python/PySpark.
Document architecture decisions and trade-offs for engineering and business audiences.
Partner with the existing CCARS pipeline team on parallel-run validation, cutover planning and legacy pipeline decommissioning.

Qualifications

10+ years of designing data warehouse and lakehouse solutions.
5+ years of hands-on experience with Databricks/Delta Lake and Snowflake or API-driven ingestion.
Deep hands-on dimensional modeling expertise: Kimball star schema, fact and dimension design, grain definition, SCD Type I/II.
Proven experience designing Medallion (Bronze/Silver/Gold) architectures, including the trade-offs between pure lakehouse and hybrid lakehouse-to-DW designs.
Strong Delta Lake expertise: Delta tables, ACID transactions, Z-ordering, OPTIMIZE/VACUUM, and Databricks workload tuning at scale.
Expert-level T-SQL and Spark SQL, including complex joins, window functions, query tuning, indexing and partitioning.
Deep knowledge of relational databases (SQL Server preferred) and of OLTP versus OLAP design.
Track record enforcing data integrity across pipeline boundaries: referential integrity, deduplication, reconciliation, checksum/hash validation, and detecting upstream schema drift.
Experience consuming REST APIs at scale, including pagination, rate limiting, async job patterns and endpoint-specific freshness.
Experience ingesting from external Snowflake sources and non-standardized vendor exports (flat files, SFTP, vendor APIs).
Experience designing high-volume pipelines (millions of records per day, hourly-to-real-time) with backpressure, retry and failure isolation.
Experience with orchestration tools such as Azure Data Factory or Databricks Workflows.
Proficiency in Python or PySpark, and familiarity with Azure (Databricks, ADF, SQL Managed Instance, Key Vault).
Strong communication skills for documenting decisions and explaining trade-offs to technical and business audiences.

Nice to have:

Prior experience with Genesys Cloud, Genesys A3S or Verint data models.
Contact centre or telephony domain knowledge: call detail records, agent activity, quality evaluations, IVR and routing.
Experience running parallel-run migration strategies, with legacy and new systems live simultaneously during cutover.
Experience with enterprise schedulers such as AutoSys is a plus.

Additional Information

We offer:

Culture of Relentless Performance: join an unstoppable technology development team with a 99% project success rate and more than 30% year-over-year revenue growth.
Competitive Pay and Benefits: enjoy a comprehensive compensation and benefits package, including health insurance, and a relocation program.
Work From Anywhere Culture: make the most of the flexibility that comes with remote work.
Growth Mindset: reap the benefits of a range of professional development opportunities, including certification programs, mentorship and talent investment programs, internal mobility and internship opportunities.
Global Impact: collaborate on impactful projects for top global clients and shape the future of industries.
Welcoming Multicultural Environment: be a part of a dynamic, global team and thrive in an inclusive and supportive work environment with open communication and regular team-building company social events.
Social Sustainability Values: join our sustainable business practices focused on five pillars, including IT education, community empowerment, fair operating practices, environmental sustainability, and gender equality.
Miratech is an equal opportunity employer and does not discriminate against any employee or applicant for employment on the basis of race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity, or any other protected status under applicable law.

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More about this job

Responsibilities

Design and own the end-to-end data platform, including source ingestion, Bronze/Silver/Gold transformations, and a Kimball-style reporting model for Genesys, Verint, and related data. Build reliable, auditable Databricks pipelines; define data quality, orchestration, and recovery standards; and lead parallel-run validation and legacy pipeline decommissioning with the existing team.

Requirements

Requires 10+ years designing data warehouse and lakehouse solutions, including at least five years of hands-on Databricks/Delta Lake experience and strong Snowflake or API-ingestion experience. Candidates should have deep dimensional modeling, SQL, Python/PySpark, pipeline integrity, orchestration, and Azure expertise, along with the ability to communicate architectural decisions to technical and business audiences.

Skills

Data Architecture
Databricks
Delta Lake
Snowflake
Kimball Dimensional Modeling
Medallion Architecture
T-SQL
Spark SQL
Python
PySpark
Azure Data Factory
Data Pipeline Design
REST API Ingestion
Data Integrity and Reconciliation
Data Orchestration
Contact Center Data

Benefits

Health Insurance
Relocation Program
Professional Development Opportunities
Certification Programs
Mentorship
Internal Mobility Opportunities

Visa sponsorship

Not detected in the job text

Keywords

Databricks
Delta Lake
Snowflake
Azure Data Factory
Azure
SQL Server
SQL Managed Instance
Key Vault
T-SQL
Spark SQL
Python
PySpark
Genesys A3S
Genesys Cloud
Verint Workforce Management
REST APIs
SFTP
Medallion Architecture
Kimball Star Schema
Dimensional Modeling
Slowly Changing Dimensions
Data Warehousing
Lakehouse Architecture
Data Ingestion
Data Orchestration
Data Integrity
Data Reconciliation
Schema Drift
Parallel-Run Migration
Contact Center Analytics

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