Family Dollar
United States
Data Engineer
- Big Data
- Cloud
- Cloud Native
- Data Analysis
AI Summary
Design and own the end-to-end data platform for APEX using a Medallion architecture on Databricks and a Kimball reporting layer. Define ingestion, transformation, data integrity, orchestration, and Gold-layer dimensional modeling across Genesys Snowflake and Verint sources. Requires 10+ years of data warehouse/lakehouse experience, 5+ years with Databricks/Delta Lake and Snowflake or API-driven ingestion, and expert SQL.
Key Highlights
Hybrid role requiring 2 days per week in a downtown Toronto office
Own end-to-end data platform architecture for APEX
Medallion architecture on Databricks into a Kimball reporting layer
Genesys A3S Snowflake and Verint WFM data sources
Parallel run and legacy pipeline decommissioning
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Key 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.
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.
Technical Skills Required
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Benefits & Perks
health insurance
relocation program
professional development opportunities
mentorship
internal mobility
internship opportunities
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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.
Job Description
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.
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