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Early. Similar jobs usually come down between day 7 and day 54.
At Miratech, jobs usually come down by about day 10.
From 7,992 similar postings that came down, and 47 of Miratech’s. Coming down is not always a hire.
Mississauga, Ontario, Canada
Actively hiring, first seen by us 1 day agoThis 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 type in the employer’s posting: Full-timeFrom the employer’s posting
Design Bronze/Silver/Gold data flows and ingestion cadence for Genesys Snowflake and Verint sources
Build the Gold-layer Kimball star schema with grain, facts, dimensions and SCD handling
Define data integrity checks, batch control and failure recovery for each pipeline
Design API ingestion handling pagination, rate limits and async submit-poll-retrieve jobs
Partner with the CCARS team on parallel run, cutover and legacy decommissioning
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)
Define data integrity checks, batch control, idempotency and failure-recovery patterns for each pipeline
Design API ingestion that handles pagination, rate limits, asynchronous submit-poll-retrieve jobs and per-entity fan-out at scale.
Partner with the existing CCARS pipeline team on parallel-run validation, cutover planning and legacy pipeline decommissioning.
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.
Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 1
Early. Similar jobs usually come down between day 7 and day 54.
At Miratech, jobs usually come down by about day 10.
From 7,992 similar postings that came down, and 47 of Miratech’s. Coming down is not always a hire.
13 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- 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.
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Yes. We’ve followed 6 other Senior Data Architect jobs there since October 2026. One came down after 3 days. 5 are still up.
Large employers often post one title for several teams, so these can be separate openings.
New Data Leadership postings at the employers we follow are up 7% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.
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:
Nice to have:
We offer:
* 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.
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%.
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Mississauga, 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:
- 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.
No clear work-authorization passage found. Eligibility is unconfirmed.