SENIOR DATA PLATFORM ENGINEER

SENIOR DATA PLATFORM ENGINEER

Snowflake Platform Engineering | DataOps | DevOps

LOCATION Remote / TEAM Data Platform Engineering
REPORTS TO Manager, Data Platform Engineering Contract
About the role
We are seeking a Senior Snowflake Data Platform Engineer to design, build, secure, optimize, and operate an enterprise
data platform in a regulated financial services environment. This role combines hands-on Snowflake engineering with
Azure Data Factory operations, vendor integrations, cloud networking, CI/CD, observability, data quality, and database
migration responsibilities.
This is an end-to-end ownership role. The engineer will be accountable for reliable nightly processing, governed data
delivery, production-ready deployment practices, proactive monitoring, and sustainable operating standards across
Snowflake and Azure.

What you'll own
1. Snowflake platform engineering
Design and implement Snowflake databases, schemas, virtual warehouses, resource monitors, storage integrations,
network policies, and secure data-sharing patterns.
Develop and maintain tables, views, materialized views, streams, tasks, Snowpipe, Dynamic Tables, stored
procedures, Snowpark components, and Time Travel or zero-copy cloning patterns.
Optimize query performance, warehouse sizing, clustering strategies, caching behavior, concurrency, storage, and
compute consumption.
Implement workload isolation, tagging, chargeback or show-back reporting, budget controls, and cost alerts.
Establish platform standards for naming, object lifecycle, release management, and operational support.
2. Azure Data Factory at enterprise scale
Operate, tune, and extend a production ADF estate supporting large-scale ingestion, transformation, and data
distribution workloads.
Design reusable, metadata-driven pipelines using parameterized datasets, configuration tables, shared templates,
and restartable processing patterns.
Manage Azure, Self-Hosted, and SSIS Integration Runtimes, including availability, upgrades, capacity planning, and
performance troubleshooting.
Own triggers, dependencies, concurrency, retry, idempotency, watermarking, and recovery behavior.
Diagnose throttling, Integration Runtime saturation, cascading failures, poison files, schema drift, and redundant data
movement.
3. Data integration: SFTP, APIs, batch, CDC, and streaming
Onboard and operate inbound and outbound SFTP feeds with varying file formats, naming standards, delivery
windows, and service-level expectations.
Manage SSH keys, PGP encryption, IP allow-listing, certificates, and secrets through Azure Key Vault and managed
identities.
Integrate REST and SOAP APIs using OAuth 2.0, client credentials, mTLS, API keys, and token-refresh patterns
through ADF, Azure Functions, or Logic Apps.
Handle pagination, rate limiting, backoff, partial failures, incremental extraction, CDC, and micro-batch patterns.
Implement file-arrival controls, late or missing file alerts, checksums, archival, retention, duplicate detection, and
quarantine handling.

DATA PLATFORM ENGINEERING | JOB DESCRIPTION

Senior Snowflake Data Platform Engineer | Confidential hiring document

4. Data quality, reconciliation, and modeling
Implement row-count reconciliation, source-to-target validation, duplicate detection, referential integrity, data profiling,
freshness controls, and exception reporting.
Build automated, metadata-driven data quality rules with thresholds, alerting, audit trails, and evidence retention.
Design Raw, Curated, and Consumption layers and scalable dimensional, star, snowflake, and canonical data
models.
Support analytics-ready data products, semantic layers, and reporting solutions for Power BI, Sisense, Tableau, and
similar tools.
Collaborate with business, risk, finance, compliance, and data governance teams to define trusted data and
acceptance criteria.
5. Security, governance, and regulatory controls
Implement role-based access control, least privilege, segregation of duties, masking policies, row access policies,
encryption, tagging, and secure views.
Support PCI DSS, SOX, OCC, privacy, audit evidence, change control, retention, and internal security requirements.
Enable data lineage, classification, cataloging, ownership, and policy enforcement using Microsoft Purview or
comparable tooling.
Ensure production changes are traceable, reviewed, tested, approved, and supported by rollback procedures.
6. Networking, CI/CD, and infrastructure as code
Design Azure DevOps YAML pipelines for Snowflake objects, ADF artifacts, database changes, Azure Functions,
and infrastructure deployments.
Implement DEV-to-UAT-to-PROD promotion with parameterization, approval gates, artifact versioning, source
control, and rollback.
Troubleshoot VNets, subnets, NSGs, private endpoints, Private Link, service endpoints, DNS, private DNS zones,
VPN or ExpressRoute, firewalls, and Self-Hosted IR network paths.
Build reproducible environments using Bicep, ARM, Terraform, Snowflake CLI, schemachange, Flyway, Liquibase,
dbt, or comparable deployment tools.
7. Database and warehouse migrations
Plan and execute migrations from SQL Server, Oracle, PostgreSQL, DB2, Sybase, and legacy data warehouses into
Snowflake and Azure targets.
Use assessment, backup and restore, replication, CDC, staged file loading, and reconciliation approaches
appropriate to cutoff windows and downtime tolerance.
Address linked servers, SQL Agent jobs, SSIS packages, stored procedure incompatibilities, data type differences,
collation, historical loads, and undocumented ETL.
Rehearse cutovers with validation, business acceptance criteria, audit evidence, and tested rollback plans.
8. Observability and production operations
Build monitoring with Snowsight, Access History, Account Usage, Event Tables, Azure Monitor, Log Analytics, KQL,
alert rules, and action groups.
Develop operational dashboards for pipeline health, SLA attainment, file arrival, warehouse utilization, cost trends,
data quality, and Integration Runtime health.
Reduce alert noise through actionable thresholds, dependency-aware notifications, and automated recovery where
appropriate.
Participate in on-call support, incident response, root cause analysis, blameless postmortems, problem management,
and permanent remediation.
Maintain runbooks, support procedures, architecture documentation, and vendor-facing technical communications.
Required qualifications
Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related discipline, or equivalent
practical experience.
7+ years of experience in data engineering, platform engineering, database engineering, or DevOps, including 3+
years of hands-on Snowflake production experience.