Enterprise data pipelines, lakehouse, and AI-ready infrastructure
Cymetrix is a data engineering consulting partner with delivery centres in India and client offices in the USA, UK, Poland, and Japan. We design, build, and scale enterprise data pipelines, cloud data lakehouses, and real-time streaming architectures, enabling organisations to move from fragmented, manually maintained data systems to governed, production-grade infrastructure ready for analytics, ML, and AI.
Our practice spans the full stack, from data ingestion using Fivetran and Auto Loader, to transformation using dbt and Delta Live Tables on Databricks, to real-time streaming using Apache Kafka, to BI connectivity using Looker and Tableau. Whether you are building your first pipeline, migrating from legacy ETL tools, or scaling a lakehouse to support ML and generative AI, our consulting team delivers solutions built for long-term scale, governance, and performance.
What sets Cymetrix apart is our connected data architecture: we build pipelines that do not stop at the data warehouse. We connect your data engineering layer to Salesforce Data 360 for CRM data unification, Informatica for enterprise master data quality, and TextQL Ana for natural language analytics, so your data infrastructure serves sales, marketing, and customer experience operations directly.
Our Data Engineering Services
End-to-end data engineering consulting, from strategy and architecture to pipeline development, cloud migration, real-time streaming, and managed services, built for enterprise scale.
Assess your data estate, define the right architecture, and build a phased roadmap from raw ingestion to AI-ready analytics.
•Conduct a data estate assessment: inventory of existing schemas, pipelines, data volumes, and technical debt to baseline readiness.
•Design the Medallion architecture: Bronze, Silver, and Gold layer definitions aligned to your business domains.
•Select and size cloud storage and compute: ADLS Gen2, S3, or GCS matched to platform and workload, with Databricks workspace topology and cluster configuration.
•Deliver a phased roadmap from foundational pipeline infrastructure to ML-ready Gold layer and AI activation, covering ingestion (Fivetran, Auto Loader), transformation (dbt, Delta Live Tables), and orchestration (Airflow).
Build robust batch and streaming pipelines across cloud and hybrid environments.
• Build Delta Live Tables (DLT) pipelines: declarative ETL/ELT with built-in data quality enforcement, lineage, and automatic dependency resolution.
• Develop dbt transformation layers: SQL-based modular transformations with version control, testing, and lineage documentation.
• Set up Fivetran connectors for ingestion from Salesforce, SAP, Workday, NetSuite, and 300+ enterprise sources.
• Migrate legacy ETL pipelines from Informatica PowerCenter, SSIS, or Talend to Databricks-native or cloud-native architecture.
Migrate legacy data warehouses and on-prem systems to modern cloud platforms without disrupting production workloads.
•Assess existing schemas, stored procedures, views, and query patterns with complexity scoring before migration begins.
•Migrate on-premises data warehouses (Teradata, Oracle, SQL Server) to Databricks Lakehouse with Delta Lake format.
•Execute zero-downtime migration using parallel running, incremental table cutover, and rollback checkpoints.
•Validate all migrations with row count reconciliation, query result comparison, and stakeholder sign-off reporting.
Architect and build event-driven pipelines for real-time data activation.
•Design and build Apache Kafka cluster architecture: topic design, partitioning strategy, retention policies, and consumer group configuration.
•Develop Spark Structured Streaming pipelines on Databricks with stateful transformations and exactly-once guarantees.
•Implement Change Data Capture (CDC) pipelines using Debezium from Postgres, MySQL, Oracle, and SQL Server.
•Activate enriched streaming events into Salesforce Data 360 and marketing automation platforms in real time.
Design and build a unified data lakehouse on Databricks combining data warehousing, data engineering, and ML/AI on a single open platform.
•Design Delta Lake tables with schema enforcement, ACID transactions, time travel, and compaction configuration.
•Implement the Medallion architecture: Bronze raw ingest, Silver cleansed, Gold business-domain-ready tables.
•Configure Unity Catalog: metastore setup, catalog and schema hierarchy, row-level and column-level security.
Deploy TextQL Ana on top of Gold tables for natural language analytics without SQL dependency.
Implement monitoring, alerting, data quality enforcement, and lineage tracking across all pipelines.
•Integrate Great Expectations for automated data quality tests at every pipeline stage with failure alerting.
•Define and enforce data contracts: schema and quality agreements between data producers and consumers, versioned and tracked.
•Track end-to-end data lineage from raw source through transformations to dashboard and ML model.
•Configure SLA alerting for pipeline failures, late arrivals, and data quality breaches.
Ongoing pipeline support, monitoring, performance optimisation, and cost governance.
•Manage cluster autoscaling, compute right-sizing, and spot instance strategies for cost reduction.
•Monitor Databricks Workflows and Airflow DAGs with automated incident response.
•Schedule Delta Lake compaction (OPTIMIZE, VACUUM, Z-ORDER) to maintain query performance at scale.
•Deliver monthly platform health reports covering pipeline performance benchmarks, cost analysis, and capacity planning.
How Cymetrix Powers
Brand Success?
The Cymetrix data engineering stack: pipelines, CRM, data quality, and AI
Most data engineering partners deliver pipelines. Cymetrix delivers connected data infrastructure, linking your pipelines to your CRM, master data quality layer, and AI query interface in one unified architecture.
Data engineering + Salesforce Data 360
We build bidirectional pipelines between your data layer and Salesforce Data 360. Enriched customer attributes, ML scores, and aggregated analytics flow back into CRM automatically. Your sales and marketing teams operate from live, data-enriched records rather than stale exports.
Data engineering + Informatica MDM
Informatica, now part of the Salesforce stack following its November 2025 acquisition, provides enterprise master data management and quality enforcement. Cymetrix connects Informatica MDM rules to your Databricks Silver transformation layer, ensuring every analytics model and ML workload runs on governed, trusted data.
Data engineering + Databricks + TextQL
We build your data lakehouse on Databricks and deploy TextQL Ana on top, enabling business leaders to ask complex questions in plain English and receive governed answers directly from your production data, without SQL dependency, without analyst queues, and without additional infrastructure.
Cymetrix Industry Solutions Powered by Data Engineering
Customer-facing data intelligence across every sector, connecting data pipelines to CRM, marketing, and customer experience operations.
•Customer 360 pipeline: unifying CRM, transaction, and product data into a governed lakehouse for sales team analytics.
•Customer churn prediction: ML models on Databricks identifying at-risk retail banking and insurance customers before they lapse.
•Next-best-offer pipeline: personalised product suggestions for retail banking, wealth, and insurance customers using real-time scoring.
•Patient engagement analytics: unifying appointment, interaction, and care journey data for personalised outreach programmes.
•Pharma commercial analytics: connecting Salesforce CRM rep activity, HCP interactions, and product usage for territory performance.
•Clinical trial recruitment pipeline: identifying eligible patient cohorts from unified data to accelerate trial enrolment.
•Product usage + CRM + support unification: connecting telemetry, Salesforce, and ticketing for customer health scoring.
•SaaS revenue analytics: ARR, NRR, churn, and cohort analysis with Salesforce as the source of record.
•Customer expansion pipeline: predicting upsell and cross-sell opportunities from product usage and CRM signals.
•Dealer and distributor analytics: unifying dealer sales, order pipeline, and CRM data for territory performance reporting.
•Salesforce CRM + ERP integration: connecting account and opportunity data with production systems for real-time sales pipeline visibility.
•Warranty and service data pipeline: connecting claims, service tickets, and customer feedback for customer experience analytics.
•Customer 360 lakehouse: unifying commerce, loyalty, mobile, and in-store data in a single Databricks lakehouse.
•ML personalisation pipeline: product recommendation models trained on unified customer behavioural data.
•Marketing attribution pipeline: multi-touch attribution across paid, organic, email, and CRM channels using Delta Live Tables.
Why choose Cymetrix for data engineering?
Full-stack data engineering
From ingestion to transformation to ML activation, we build the complete data stack, not just individual pipeline components.
Connected to CRM and AI
Every pipeline we build connects to Salesforce Data 360, Informatica, and TextQL, so your data infrastructure serves business operations, not just data teams.
Technical depth
Named technologies, specific capabilities, and production-grade delivery, not generic data platform consulting.
Global Delivery
Engineering centres in Mumbai and Delhi NCR. Client engagement in USA, UK, and Poland. We work to your timezone.
Power Your Data Projects with On-Demand Data Engineering Talent
Whether you need to scale a data engineering team rapidly, fill a pipeline architect gap on a live project, or build in-house data platform capability without permanent headcount, Cymetrix's on-demand model gives you access to certified data engineers, Databricks architects, dbt specialists, and streaming engineers on flexible terms, integrated directly into your team, tools, and delivery cadence.
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FAQs
Ready to build production-grade Data Engineering?
Whether you are starting from scratch, migrating from legacy ETL tools, or scaling a data lakehouse to support ML and generative AI, Cymetrix has the architecture expertise, delivery track record, and connected data stack to take you there. Talk to our data engineering consulting team and tell us where you are in your data journey.
Allied For Success: Our Partnerships
We partner with global technology leaders across CRM, cloud data, AI and integration ecosystems to strengthen our enterprise delivery model.
