Senior Data Architect
North York, Ontario, Canada
- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
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:
Read the full posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingDesign the Bronze/Silver/Gold data flow and ingestion standards per source
Design the Gold-layer Kimball star schema, grain and SCD handling
Design API and file ingestion with pagination, rate limits and schema drift tolerance
Define data integrity checks, batch control and failure recovery for each pipeline
Partner with the CCARS team on parallel run, cutover and decommissioning
From the employer’s posting
Design the Bronze/Silver/Gold data flow for the new Genesys A3S Snowflake and Verint sources
Design the Gold-layer Kimball star schema (facts, dimensions, grain, SCD Type I/II)
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
Partner with the existing CCARS pipeline team on parallel-run validation, cutover planning and legacy pipeline decommissioning.
What you’ll bring
All qualificationsCore experience
- 10+ years of designing data warehouse and lakehouse solutions.
- Prior experience with Genesys Cloud, Genesys A3S or Verint data models.
- 5+ years of hands-on experience with Databricks/Delta Lake and Snowflake or API-driven ingestion.
- Experience running parallel-run migration strategies, with legacy and new systems live simultaneously during cutover.
- Proven experience designing Medallion (Bronze/Silver/Gold) architectures, including the trade-offs between pure lakehouse and hybrid lakehouse-to-DW designs.
- Deep knowledge of relational databases (SQL Server preferred) and of OLTP versus OLAP design.
Preferred experience
- Experience with enterprise schedulers such as AutoSys is a plus.
Qualification wording
10+ years of designing data warehouse and lakehouse solutions.
Prior experience with Genesys Cloud, Genesys A3S or Verint data models.
5+ years of hands-on experience with Databricks/Delta Lake and Snowflake or API-driven ingestion.
Experience running parallel-run migration strategies, with legacy and new systems live simultaneously during cutover.
Proven experience designing Medallion (Bronze/Silver/Gold) architectures, including the trade-offs between pure lakehouse and hybrid lakehouse-to-DW designs.
Deep knowledge of relational databases (SQL Server preferred) and of OLTP versus OLAP design.
Experience with enterprise schedulers such as AutoSys is a plus.
Tools in this posting
- Python
- SQL
- Azure
- Databricks
- Delta Lake
- Snowflake
- Spark
- SQL Server
- PySpark
Source — Tool mentions in context
- 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.
- 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.
- 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.
- 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.
- 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.
- 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).
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.
- 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.
- 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.
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.
- 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.
- 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.
Posting record
Report an errorActively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 27, 2026 · 2 days ago
- Recorded sightings
- 26
- Last seen by us
- Oct 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
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.
Company 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%.
Source details
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
North York, Ontario, Canada
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:
More source context
- 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.
More relevant text appears in the full description.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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