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Pune, India
Live, first seen by us 29 days agoLocation type: HybridFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: Agentic Software Engineering › Consumer Experience › Digital SolutionsFrom the employer’s posting
Design replacement ingestion that runs natively inside each customer's Snowflake account
Translate legacy ETL transformations into Snowflake-native pipelines
Build data models and pipelines with explicit per-tenant isolation
Decide which legacy technical debt to carry forward, redesign, or retire
Validate the new pipeline under realistic production load patterns
design and build the replacement for the current endpoint-to-cloud-function-to-streaming-queue-to-ETL-to-warehouse path, moving ingestion natively into each customer's own Snowflake account
translate existing transformation logic covering activity, meeting/event, network context, and system metadata data into Snowflake-native pipelines
build data models and pipeline logic that hold up under a cross-account, multi-tenant distribution model
deciding case by case what gets carried forward, redesigned, or retired
Validate against real production data patterns — batch sizes, sync frequencies, offline-queue backlogs
Experience building and distributing applications through a cloud data platform's own marketplace or listing model.
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Day 29
Similar jobs usually come down between day 6 and day 54.
From 10,782 similar postings that came down. Coming down is not always a hire.
8 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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Required skills & experience - 5+ years as a data engineer with hands-on Snowflake experience — native transformation and orchestration features, not just SQL. - Real experience migrating an existing production ETL pipeline to a cloud-native target — not a from-scratch build.
Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively. We are looking for a Senior Data Engineer to join a team migrating a production SaaS data platform off a legacy ETL/streaming-based pipeline and onto a Snowflake Native Application built for self-serve distribution and per-tenant data isolation. This isn't a greenfield build — it's a migration with real legacy constraints. You'll be working from an existing production system that has already been audited in detail, and turning those findings into a working Snowflake-native data platform. You should be comfortable reading someone else's architecture, spotting where it breaks down at scale or under multi-tenant isolation requirements, and redesigning around it.
We are looking for a Senior Data Engineer to join a team migrating a production SaaS data platform off a legacy ETL/streaming-based pipeline and onto a Snowflake Native Application built for self-serve distribution and per-tenant data isolation. This isn't a greenfield build — it's a migration with real legacy constraints. You'll be working from an existing production system that has already been audited in detail, and turning those findings into a working Snowflake-native data platform. You should be comfortable reading someone else's architecture, spotting where it breaks down at scale or under multi-tenant isolation requirements, and redesigning around it. What you'll do
What you'll do - Re-architect ingestion — design and build the replacement for the current endpoint-to-cloud-function-to-streaming-queue-to-ETL-to-warehouse path, moving ingestion natively into each customer's own Snowflake account so the platform's data-sovereignty story is true end to end. - Migrate legacy ETL logic — translate existing transformation logic covering activity, meeting/event, network context, and system metadata data into Snowflake-native pipelines using the right combination of native transformation tooling and orchestration.
- Re-architect ingestion — design and build the replacement for the current endpoint-to-cloud-function-to-streaming-queue-to-ETL-to-warehouse path, moving ingestion natively into each customer's own Snowflake account so the platform's data-sovereignty story is true end to end. - Migrate legacy ETL logic — translate existing transformation logic covering activity, meeting/event, network context, and system metadata data into Snowflake-native pipelines using the right combination of native transformation tooling and orchestration. - Design for per-tenant isolation — build data models and pipeline logic that hold up under a cross-account, multi-tenant distribution model, with tenant boundaries addressed explicitly at the schema, pipeline, and secret-management level.
- Work through known technical debt — shared credentials baked into client-side builds, build-time-only configuration with no live tenant provisioning, inconsistent cross-platform data-capture parity — deciding case by case what gets carried forward, redesigned, or retired. - Rebuild the platform's core data model — activity, event, network, and metadata — preserving the analytics the business depends on while moving underlying storage and processing into Snowflake. - Validate against real production data patterns — batch sizes, sync frequencies, offline-queue backlogs — captured during discovery to ensure the new pipeline design holds up under realistic load.
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Yes. We’ve followed one other Senior Data Engineer job there since June 2026. It came down after 23 days.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes.
Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively.
We are looking for a Senior Data Engineer to join a team migrating a production SaaS data platform off a legacy ETL/streaming-based pipeline and onto a Snowflake Native Application built for self-serve distribution and per-tenant data isolation.
This isn't a greenfield build — it's a migration with real legacy constraints. You'll be working from an existing production system that has already been audited in detail, and turning those findings into a working Snowflake-native data platform. You should be comfortable reading someone else's architecture, spotting where it breaks down at scale or under multi-tenant isolation requirements, and redesigning around it.
Re-architect ingestion — design and build the replacement for the current endpoint-to-cloud-function-to-streaming-queue-to-ETL-to-warehouse path, moving ingestion natively into each customer's own Snowflake account so the platform's data-sovereignty story is true end to end.
Migrate legacy ETL logic — translate existing transformation logic covering activity, meeting/event, network context, and system metadata data into Snowflake-native pipelines using the right combination of native transformation tooling and orchestration.
Design for per-tenant isolation — build data models and pipeline logic that hold up under a cross-account, multi-tenant distribution model, with tenant boundaries addressed explicitly at the schema, pipeline, and secret-management level.
Work through known technical debt — shared credentials baked into client-side builds, build-time-only configuration with no live tenant provisioning, inconsistent cross-platform data-capture parity — deciding case by case what gets carried forward, redesigned, or retired.
Rebuild the platform's core data model — activity, event, network, and metadata — preserving the analytics the business depends on while moving underlying storage and processing into Snowflake.
Validate against real production data patterns — batch sizes, sync frequencies, offline-queue backlogs — captured during discovery to ensure the new pipeline design holds up under realistic load.
Document migration decisions clearly enough to be defended internally, to downstream customers, and through a formal marketplace review process.
5+ years as a data engineer with hands-on Snowflake experience — native transformation and orchestration features, not just SQL.
Real experience migrating an existing production ETL pipeline to a cloud-native target — not a from-scratch build.
Working knowledge of streaming and event pipelines.
Comfortable reading and reasoning about a system's security model — encryption at rest and in transit, key management, multi-tenant secret handling — well enough to flag when a proposed design reintroduces a previously identified gap.
Familiarity with a major cloud provider's function/PaaS services, as parts of the migration will need to interoperate with the current production system during transition.
Experience designing for multi-tenant SaaS data isolation — schema-per-tenant, row-level security, or equivalent patterns.
Experience building and distributing applications through a cloud data platform's own marketplace or listing model.
Background in workforce analytics, activity monitoring, or similar behavioral/event data domains — application/window/URL activity, meeting data, network context.
Exposure to BI tooling migration alongside an underlying data platform move.
When you join Solvd, you'll…
Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation.
Be part of a global team with equal opportunities for collaboration across continents and cultures.
Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards.
Ready to make an impact?
If you're excited to build things that matter, champion responsible AI, and grow with some of the industry’s sharpest minds. Apply today and let’s innovate together.
Solvd is an equal opportunity employer.
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Pune, India
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