ML Engineer

Job Title :ML Engineer
Job Type :W2 Contract
Bill Rate:$70/Hr on w2
Location: Tennessee Colony, TX, USA
Duration:10 months
Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD

Responsibilities:
Design and build Snowflake Semantic Views that define logical tables,
relationships, dimensions, facts, and metrics for core network domains
and datasets. Translate raw network counters into standardized KPIs
aligned with 3GPP measurement definitions
Model time-series behavior correctly. This includes granularity
(5-min, 15-min, hourly, daily), time-zone handling, late-arriving data,
and aggregation rules for additive, semi-additive, and ratio-based KPIs.
For ratio KPIs, this means re-aggregating the numerator and denominator
rather than averaging ratios.
Build conformed dimensions such as network element, node type, vendor,
region/site, time, and service/slice, so KPIs can be sliced consistently
across domains.
Author and maintain synonyms, descriptions, and sample questions so
the semantic views work well with Cortex Analyst and natural-language
querying.
Work with the data engineering team to understand the ingestion
architecture (e.g., Snowflake Kafka Connector, Snowpipe Streaming,
Openflow, Dynamic Tables, Streams, Tasks etc.). Ensure the semantic
layer is built on stable, well-defined interfaces rather than volatile
raw tables.
Implement automated drift detection covering schema changes (new,
renamed, or dropped columns, and data type changes), new network
elements or counters, and changes to KPI formulas. Use monitoring,
Snowflake Alerts, and event-driven checks.
Define and enforce data contracts between ingestion and semantic
layers, including versioning, change notification, and
backward-compatibility rules.
Monitor data freshness and latency SLAs so that semantic views reflect
near-real-time data. Configure Dynamic Table target lag or equivalent
mechanisms appropriately.
Manage semantic view definitions as code, with CI/CD pipelines for
deployment across dev, test, and prod.
Implement automated testing for KPI logic, including unit tests on
formulas, row-count and null checks, threshold/anomaly tests, and
regression tests against golden datasets.
Maintain a KPI catalog and business glossary documenting each metric's
definition, formula, source counters, owner, and change history.
Optimize query performance and cost through clustering, warehouse
sizing, materialization choices, and monitoring of compute consumption.
Work closely with data engineers on ingestion design and with
BI/analytics teams (Power BI, Tableau, etc.) who consume the semantic
layer.
Act as the point of contact for questions about metric definitions,
resolving discrepancies across teams. Requirements:
Strong hands-on experience with Snowflake, including advanced SQL,
Semantic Views and/or Cortex Analyst semantic models, Dynamic Tables,
Streams and Tasks, Snowpipe/Snowpipe Streaming, and performance tuning.
Proven experience building semantic layers or metrics layers. Relevant
tools include Snowflake Semantic Views, dbt Semantic Layer/MetricFlow,
AtScale, LookML, or Power BI semantic models.
Solid dimensional modeling skills (Kimball star/snowflake schemas) and
experience modeling high-volume time-series data.
Working knowledge of telecom core network architecture familiarity
with performance management counters and KPIs, is strongly recommended.
Understanding of streaming data concepts: Kafka topics and partitions,
event time vs. processing time, late and out-of-order data, and
exactly-once semantics.
Exposure to Python/Snowpark for automation and data quality
frameworks.
Strong analytical and communication skills, with the ability to
explain technical metric logic to non-technical stakeholders.

Equal Opportunity Employer : We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.