Senior Data Engineer

We are looking for an experienced Senior CRM Data Integration Architect to lead data engineering and integration initiatives for customer lifecycle marketing platforms. The role involves designing and implementing data flows between cloud data warehouses, event\-streaming systems, APIs, and CRM/marketing automation platforms.

The ideal candidate will have strong hands\-on expertise in Databricks, Snowflake, Kafka, Python, SQL, and at least one marketing automation platform, along with experience in solution architecture, client\-facing technical discussions, and end\-to\-end integration delivery.

Key Responsibilities

• Conduct technical discovery of existing data environments, including data warehouses, Kafka topics, APIs, microservices, and legacy systems.
• Map data sources and define source\-of\-truth matrices to establish reliable data ownership and data flows.
• Design customer identity models and relationships across multiple brands, accounts, tenants, and business entities.
• Define event taxonomies, data schemas, naming conventions, customer attributes, and payload requirements.
• Design consent and subscription architectures to manage transactional, product\-related, and marketing communication preferences.
• Architect data integrations between warehouses, streaming systems, APIs, and marketing automation platforms.
• Determine appropriate integration methods, including batch processing, real\-time streaming, and reverse ETL.
• Develop and optimize data pipelines using Databricks, Delta Lake, Spark SQL, PySpark, Snowflake, and SQL.
• Design and implement integrations using Kafka, REST APIs, webhooks, and other data exchange mechanisms.
• Plan data migration, historical data backfills, cutover activities, and implementation testing.
• Review integration outputs, validate sample payloads, troubleshoot data issues, and ensure end\-to\-end data accuracy.
• Collaborate with client engineering teams, data leads, and technical stakeholders to communicate architecture decisions and implementation requirements.
• Develop middleware, connectors, and integration jobs using Python and relevant cloud services when required.
• Ensure data security, privacy compliance, deduplication, error handling, reconciliation, and reliable data synchronization.
• Maintain technical documentation, architecture blueprints, implementation plans, decision logs, and quality assurance checklists.
• Support technical discovery calls, solution estimation, proposal development, and continuous improvement of integration practices.

Required Technical Skills

• **Data Engineering:** Strong hands\-on experience with Databricks, Delta Lake, Spark SQL, PySpark, and data pipeline development.
• **Cloud Data Warehouse:** Advanced knowledge of Snowflake, SQL, data modelling, Streams, Tasks, Snowpipe, and performance optimization.
• **Event Streaming:** Production experience with Kafka, topics, partitions, consumers, schema registry, and change data capture (CDC).
• **API Integration:** Strong knowledge of REST APIs, webhooks, authentication, pagination, rate limits, retries, and error handling.
• **Marketing Automation Platforms:** Deep hands\-on experience with at least one of Braze, Salesforce Marketing Cloud (SFMC), Customer.io, Iterable, or Klaviyo.
• **Programming:** Strong proficiency in Python and SQL; working knowledge of JavaScript or TypeScript.
• **Cloud Technologies:** Working knowledge of AWS services such as Lambda, S3, Glue, Step Functions, EventBridge, and IAM.
• **CRM and Customer Data:** Understanding of customer identity models, event schemas, consent management, subscription preferences, and data synchronization.

Pay: ₹4,000,000\.00 \- ₹4,400,000\.00 per year

Work Location: Remote