Senior Data Services Consultant

We are looking for a Senior Data Services Consultant with strong expertise in Data Integration, Workflow Automation, Data Quality, and BI & Analytics to lead enterprise data initiatives across Antsomi’s Customer Data Platform (CDP) and related solutions. You will work with complex customer data ecosystems spanning systems such as CRM, POS, Ecommerce, Loyalty, ERP, Billing, Data Warehouses, and third-party SaaS platforms . This is a senior hands-on and customer-facing role combining data integration, automation, analytics, troubleshooting, and consulting . You will lead complex data engagements, advise enterprise clients, and help develop scalable Data Services capabilities across the organization. Your role & responsibilities 1. Data Integration & Workflow Automation Lead the design and implementation of enterprise data integrations between Antsomi and customer systems. Design and build automated workflows using n8n, Apache Airflow, or similar workflow orchestration platforms . Design and operate reliable ETL/ELT workflows and production data pipelines . Integrate data through REST APIs, Webhooks, databases, SFTP, batch files, cloud storage, and other integration methods . Define appropriate integration patterns including API-based, scheduled, batch, file-based, and event-driven integrations . Design workflow scheduling, dependencies, retries, timeout handling, logging, alerting, and recovery mechanisms. Define data extraction, transformation, mapping, and loading logic across multiple enterprise systems. Work with enterprise data domains such as Customer, Transaction, Product, Subscription, Loyalty, Campaign, and Behavioral/Event data . Lead data migration and historical data ingestion when required. Review existing integrations and recommend improvements for reliability, scalability, maintainability, and operational efficiency . Own complex integration delivery from Design → Build → Test → Go-live → Monitor → Optimize . 2. Data Mapping, Quality & Governance Analyze complex source system data models and define source-to-target mappings, data dictionaries, transformation rules, and integration specifications . Define and implement data validation and reconciliation frameworks. Establish data quality rules covering completeness, accuracy, consistency, duplication, validity, and freshness . Design reusable and automated data quality checks. Lead reconciliation between customer source systems, Antsomi platforms, and downstream reporting. Investigate complex data discrepancies across multiple systems and integration layers. Support customer identity and Customer 360 data validation across multiple sources. Identify systemic data quality issues and recommend corrective and preventive actions. Define standards for data mappings, KPI definitions, validation rules, and data documentation. Contribute to Data Health and Integration Health assessment frameworks for enterprise customers. 3. BI & Analytics Lead discussions with customers and Business Solution Consultants to understand business objectives, KPIs, reporting requirements, and analytical questions . Translate business requirements into clear metrics, dimensions, calculation logic, analytical datasets, and dashboard requirements . Design and build dashboards and reports using appropriate BI and visualization tools. Write advanced SQL for data preparation, aggregation, analysis, validation, and troubleshooting. Design analytical datasets and reporting structures that support scalable reporting. Define and validate KPI calculation logic across source systems, CDP, and reporting outputs . Perform analysis across areas such as: Customer & Customer 360 Revenue & Transactions Products & Categories Customer Segmentation Campaign & Journey Performance Loyalty & Rewards Subscription Customer Behavior & Engagement Investigate and resolve discrepancies between dashboards, CDP data, analytical datasets, and customer source systems. Identify meaningful trends, anomalies, patterns, and business insights from customer data. Translate analytical findings into clear recommendations for business stakeholders. Review dashboards and analytical outputs produced by junior team members. 4. Monitoring, Troubleshooting & Reliability Own the operational health of assigned enterprise data integrations and pipelines. Monitor workflow execution, data freshness, pipeline reliability, and integration status. Lead troubleshooting and root-cause analysis for complex production data issues. Investigate failures using logs, workflow execution history, API responses, SQL queries, databases, and source data . Design appropriate retry, alerting, exception handling, and recovery mechanisms. Identify recurring operational problems and implement automated or preventive solutions. Improve observability across data pipelines and integration workflows. Coordinate incident resolution across customers, Product, Technology, and Service teams. Conduct post-incident analysis and recommend improvements to prevent recurrence. 5. Customer Data Consulting Lead customer workshops related to data requirements, data mapping, integration, reporting, analytics, and data quality . Understand customer system landscapes and business processes to recommend practical data solutions. Challenge unclear or inefficient data requirements and propose better approaches. Translate business requirements into data and integration requirements. Advise customers on data structures, integration approaches, KPI definitions, data quality, and reporting practices. Explain complex data issues and recommendations clearly to both technical and business stakeholders. Collaborate with Business Solution Consultants to ensure data solutions support the intended business use cases. Collaborate with Technical Solution Consultants on broader system architecture, APIs, identity, and integration design when required. Act as a senior Data Services advisor for complex enterprise customer engagements. 6. Team & Capability Development Mentor Data Services Specialists . Review integration designs, workflows, SQL, data mappings, dashboards, KPI definitions, and other key deliverables. Establish reusable workflow templates, integration patterns, SQL libraries, data quality frameworks, dashboard templates, and technical standards . Improve delivery standards for testing, monitoring, documentation, and production readiness. Identify opportunities to automate repetitive implementation, validation, reporting, and operational activities. Contribute to Data Services playbooks, best practices, and internal knowledge sharing. Help improve the overall technical and analytical capability of the Data Services team. Your skills & qualifications Must-have 4+ years of hands-on experience in Data Integration, Automation Engineering, Data Engineering, BI/Data Analytics, or closely related roles. Strong hands-on experience with n8n, Apache Airflow, or similar workflow orchestration/automation platforms . Strong understanding of workflow orchestration, scheduling, dependency management, retries, logging, monitoring, alerting, and error handling . Strong hands-on experience with REST APIs, Webhooks, JSON, SQL, and relational databases . Proven experience designing and operating ETL/ELT workflows and production data pipelines . Strong experience with data mapping, transformation, validation, reconciliation, and data quality across multiple systems. Advanced SQL skills for data transformation, analysis, reconciliation, and troubleshooting. Experience designing or maintaining dashboards, analytical datasets, reports, and KPI logic . Ability to translate business questions into data requirements, metrics, analytical logic, and reporting solutions . Strong understanding of different integration patterns including API, batch, scheduled, file-based, and event-driven integrations . Proven ability to troubleshoot complex data and integration issues using logs, API responses, SQL, workflow history, and source data. Experience independently owning data integration delivery from Design → Build → Test → Go-live → Monitor → Optimize . Ability to design reliable workflows considering failure scenarios, retries, idempotency, dependencies, and data consistency . Strong system thinking, analytical thinking, and root-cause analysis skills. Ability to create clear integration designs, data mappings, data dictionaries, workflow diagrams, KPI definitions, and technical documentation . Ability to communicate effectively with both business and technical stakeholders. Experience leading customer or stakeholder discussions related to data and integration. Good English communication skills for customer workshops, technical discussions, presentations, and documentation. Nice to Have Experience with BI and visualization platforms such as Power BI, Looker Studio, Tableau, Metabase , or similar technologies. Experience with databases and analytical platforms such as BigQuery, PostgreSQL, MySQL, Snowflake, StarRocks , or similar technologies. Experience with AWS, GCP, or Azure . Experience with Customer Data Platforms (CDP), CRM, Marketing Automation, Ecommerce, Loyalty, ERP, POS, Billing , or similar enterprise platforms. Experience with technologies such as Kafka, Airbyte, dbt, Apache NiFi, Fivetran , or similar data and integration platforms. Strong experience integrating multiple third-party SaaS platforms through APIs and Webhooks . Experience with authentication and security mechanisms such as OAuth 2.0, JWT, API Keys , and related API security concepts. Experience with Python for data processing, analysis, automation, or troubleshooting. Understanding of event-driven architecture, queues, streaming, and asynchronous processing . Understanding of data modeling, dimensional modeling, and analytical data structures . Understanding of customer identity, ident