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.

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, identity resolution, Customer 360, segmentation, and behavioral data.
• Knowledge of data governance, data quality management, or master data concepts.
• Experience working in a B2B SaaS, Professional Services, System Integration, or enterprise technology environment.
• Experience mentoring junior data or integration team members.

 

What Makes You Successful in This Role

• End-to-End Data Thinking
  You understand the complete data lifecycle — from source systems and integrations through transformation, quality, reporting, and business consumption.
• Integration Architecture Thinking
  You do not simply connect System A to System B. You consider reliability, scalability, dependencies, failure scenarios, maintainability, and operational impact.
• Automation Mindset
  You continuously look for opportunities to replace repetitive implementation and operational activities with reusable, automated workflows.
• Data & Analytical Thinking
  You care not only about whether data arrives successfully, but also whether it is correct, meaningful, and capable of answering business questions.
• Technical Depth
  You are comfortable going deep into APIs, SQL, workflows, databases, transformations, dashboards, and production issues when necessary.
• Root-Cause Ownership
  You trace problems across dashboards, datasets, pipelines, integration layers, and source systems until the actual root cause is identified and resolved.
• Business Understanding
  You understand what Customer, Transaction, Product, Loyalty, Campaign, Subscription, and Behavioral data mean to the business and how they should be used.
• Customer Consulting
  You can understand a customer's data ecosystem, challenge requirements, lead data discussions, and recommend practical solutions.
• Leadership
  You improve not only your own work but also the capability of the broader team through mentoring, reviews, reusable frameworks, and best practices.