Experience : 6.00 + years

Salary : INR 1800000-2500000 / year (based on experience)

Shift : (GMT+05:30) Asia/Kolkata (IST)

Opportunity Type : Remote

Placement Type : Full time Permanent Position

**(*Note: This is a requirement for Uplers)

**What do you need for this opportunity?

Must have skills required: Snowflake, Databricks, Rest APIs, Kafka, AWS, CDP, (Braze, Salesforce Marketing Cloud, Klaviyo, Iterable, Salesforce

Uplers is Looking for:**** CRM Data Integration Architect Warehouse, event-stream and API integration for lifecycle marketing platforms

About The Role Mavlers designs and runs lifecycle marketing programs for US and APAC brands on Braze, Salesforce Marketing Cloud, Customer.io, Iterable and Klaviyo.

Every program depends on the data underneath it: events, identity, warehouse syncs, streaming feeds and CRM integrations. This role owns that layer. You lead the data and integration workstream on client engagements end to end.

You run discovery against fragmented warehouse, Kafka and API environments, design the target identity and data model, specify how each data class reaches the marketing platform, and then QA what the client's engineering team builds against your design. When an engagement calls for it, you build the integration yourself. You are the person Mavlers puts in front of a client's data lead or CTO.

What You Will Own

- Current-state discovery and source mapping. Inventory warehouse (Snowflake / Databricks), Kafka topics, APIs, microservices and legacy sources. Produce the source-of-truth matrix before taxonomy design starts.
- Target identity and relationship model. Define IDs and relationships across person, account/contract, tenant/brand and hierarchical structures. Design structural safeguards against cross-brand or cross-tenant data leakage, including single- vs multi-workspace decisions.
- Event and attribute taxonomy. Recommend the target schema, naming rules and payload requirements from a messy or partially documented starting point, working with the CRM strategy consultant.
- Consent and subscription architecture. Keep transactional, product and marketing consent states independent; design suppression, quarantine and consent-migration logic that survives legal review.
- Integration architecture and ongoing sync. Specify how each data class reaches the MAP from warehouse, stream or API: batch vs streaming vs reverse ETL, latency, deduplication, retries, error handling and reconciliation.



Produce an ordered build sequence for the engineering team.
- Migration, backfill and implementation QA. Design historical import and cutover sequencing with acceptance criteria. Review build outputs, sample payloads and end-to-end MAP behaviour against the approved design, and sign off.
- Decision and blocker management. Maintain the decision/blocker log with owner, required decision date and impact. Chase client system owners for schemas, sample events, API specs and consent data.
- Hands-on build when required. Deliver connectors, middleware jobs, warehouse models and MAP ingestion when the client lacks capacity or a Mavlers build workstream is scoped.
- Pre-sales and practice. Scope and estimate the data/integration portion of proposals; join discovery calls; contribute reference architectures, QA checklists and connector patterns back to the BU.

Technical depth expected

- Databricks - Delta Lake, Spark SQL/PySpark, Workflows, Unity Catalog; modelling and pipeline design, cost and performance (Deep)
- Snowflake - Modelling, SQL, Streams/Tasks, Snowpipe, secure data sharing, warehouse sizing and cost control (Deep)
- Kafka / event streaming - Topics, partitions, consumers, schema registry, CDC (Debezium/Kafka Connect); has shipped a streaming integration into a customer-facing system (Deep)
- REST APIs, webhooks, export APIs - Design, build, secure and debug production integrations; pagination, rate limits, idempotency, retries; MAP export/data-feed APIs (Braze Currents, CIO Data Pipelines, Iterable exports) (Deep)
- One MAP data layer (Braze, SFMC, Customer.io, Iterable or Klaviyo) - Ingestion APIs, identity/profile model, event schema, subscription/consent objects, limits and quotas (Deep)
- Remaining MAPs in scope - Know each platform's data model, identity rules and ingestion options well enough to blueprint and review (Working)
- Salesforce (Sales/Service Cloud, Data Cloud) - Object model; REST, Bulk and Streaming APIs; Data Cloud ingestion and activation patterns (Working)
- AWS - Lambda, S3, Glue, Step Functions, EventBridge,



IAM; enough to build and review serverless middleware (Working)
- CDP / reverse ETL - Segment, mParticle, Hightouch, Census: model-to-MAP sync, incremental logic (Working)
- Middleware / iPaaS - Workato, MuleSoft, Boomi or equivalent; at least one in production (Working)
- Languages - Python and SQL required; JavaScript/TypeScript working; dbt useful (Deep)

Must-haves

- 7+ years in data engineering or integration architecture, including 2+ years on customer/marketing data systems
- Hands-on production experience on Databricks, Snowflake and Kafka (not one of the three)
- Has personally run discovery and written an integration blueprint that a client engineering team then built against
- Shipped at least one end-to-end warehouse or stream to MAP integration (Braze, SFMC, Customer.io, Iterable or Klaviyo)
- Has modelled identity across multi-entity or multi-brand structures and can explain how they prevented leakage
- Has designed or audited a consent/subscription model across transactional and marketing states
- Presents architecture to client engineering leads and defends trade-offs; writes specs engineers build from without a meeting

Nice-to-have

- Direct Customer.io integration experience (Track/Identify API, Data Pipelines, Objects model)
- Databricks Data Engineer Skilled, SnowPro Advanced, or Confluent certification
- Salesforce Data Cloud or Marketing Cloud Engineer credential
- Agency, consulting or SI background with multi-client context switching
- Privacy engineering exposure: GDPR/CCPA consent propagation across systems.

How to apply for this opportunity?

- Step 1: Click On Apply! And Register or Login on our portal.
- Step 2: Complete the Screening Form & Upload updated Resume
- Step 3: Increase your chances to get shortlisted & meet the client for the Interview!

About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well).

So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

📌 CRM Data Integration Architect (India)
🏢 Uplers
📍 India