We Own the
Entire Data Lifecycle,
Not Just Pieces of It
Data only delivers value when the platform behind it is engineered to scale. We help product companies build secure, reliable, analytics-ready data platforms across the full data lifecycle—ingestion, processing, storage, and consumption. Our data engineering teams design batch and streaming pipelines, analytics layers, and cloud-native architectures that support real-time insights without compromising reliability or cost control.
We’ve delivered data platforms that handle terabytes of data, process millions of events daily, and support both operational and analytical workloads across multiple industries.
From modernizing legacy pipelines to building new data foundations for AI and analytics, we focus on one thing: engineering data systems that perform consistently in production.
WHAT WE OFFER
End-to-end services across the data lifecycle
Data Platform Modernization
We implement modern lakehouse and warehouse architectures on S3, GCS, and Azure, integrating platforms like Snowflake, BigQuery, and Redshift to support structured and unstructured data with analytics-ready models.
- Lakehouse Architecture Design
- Cloud-Native Warehousing
- Analytics-Ready Data Models
- Structured & Unstructured Data Support
Real-Time & Streaming Data Pipelines
We engineer real-time & batch data pipelines using Kafka, Spark, and Flink to support high-throughput ingestion, data transformations, event processing, fraud detection workflows, & real-time analytics at scale.
- High-Throughput Ingestion
- Event Processing & Transformation
- Fraud & Anomaly Detection
- Hybrid Batch + Streaming
AI-Ready Data Backbone (RAG & Agentic AI)
We build data foundations that support RAG & agent-based systems, enabling vector search, unstructured data persistence, and analytics modeling to provide AI workloads with secure, real-time, access to enterprise data.
- Vector Data Enablement
- Unstructured Data Foundations
- AI-Optimized Data Modeling
- Secure AI Data Access
Cloud Data FinOps & Optimization
We reduce cloud spend by matching resources to actual demand. Our team tunes your Snowflake, Databricks, or BigQuery environments to eliminate idle capacity and lower the cost of every query and pipeline.
- Cost Visibility & Attribution
- Query & Pipeline Optimization
- Capacity Right-Sizing
- Usage Governance Controls
Security, Compliance & Governance
We build secure, compliant data platforms using industry-standard frameworks, automated governance, vulnerability assessments, and continuous monitoring to ensure audit readiness & protect sensitive at scale.
- Data Access & Privacy Controls
- Audit & Compliance Readiness
- Automated Data Governance
- Continuous Security Monitoring
Scaling, DevOps & DataOps
We implement scalable architectures using Kubernetes-based autoscaling, sharding, replication, & partitioning strategies, supported by DevOps, DataOps, & MLOps practices to ensure reliability & performance at scale.
- Elastic Scaling Architecture
- Reliable Release Pipelines
- Operational Observability
- Controlled Change Management
WHAT WE OFFER
End-to-end services across the data lifecycle
Data Platform Modernization
We implement modern lakehouse and warehouse architectures on S3, GCS, and Azure, integrating platforms like Snowflake, BigQuery, and Redshift to support structured and unstructured data with analytics-ready models.
Real-Time & Streaming Data Pipelines
We engineer real-time & batch data pipelines using Kafka, Spark, and Flink to support high-throughput ingestion, data transformations, event processing, fraud detection workflows, & real-time analytics at scale.
AI-Ready Data Backbone (RAG & Agentic AI)
We build data foundations that support RAG & agent-based systems, enabling vector search, unstructured data persistence, and analytics modeling to provide AI workloads with secure, real-time, access to enterprise data.
Cloud Data FinOps & Optimization
We reduce cloud spend by matching resources to actual demand. Our team tunes your Snowflake, Databricks, or BigQuery environments to eliminate idle capacity and lower the cost of every query and pipeline.
Security, Compliance & Governance
We build secure, compliant data platforms using industry-standard frameworks, automated governance, vulnerability assessments, and continuous monitoring to ensure audit readiness & protect sensitive at scale.
Scaling, DevOps & DataOps
We implement scalable architectures using Kubernetes-based autoscaling, sharding, replication, & partitioning strategies, supported by DevOps, DataOps, & MLOps practices to ensure reliability & performance at scale.
Customers who grew with us
OUR WORK IN ACTION
Proven Data Platforms at Scale
High-Volume AdTech Data Lake & Real-Time Analytics
Processing 60M+ impressions and 9K+ installs per day, the platform ingests massive ad events and delivers real-time analytics for an AdTech client at scale.
Enterprise FinTech Lending – Real-Time Data Architecture
Handling 500 requests/sec and 22M requests/day, the platform delivers low-latency, real-time analytics for a FinTech/Lending client to accelerate loan decisioning.
Subscription Commerce Platform – Fraud & Payment Analytics Data Lake
5TB data lake processing 100GB/day and 1M+ transactions, built for a subscription e-commerce platform with secure, high-volume fraud and payment analytics.
Financial Services Data Lake & Analytics Platform
Handling large-scale batch and real-time data, the platform delivers dashboards, KPIs, and instant insights for a financial services enterprise.
Our Partners
Customer Speak
“What I like most about Talentica is their ability to solve tough, cutting-edge problems with skilled engineers who are proactive and committed. They’ve consistently delivered high-quality products on tight timelines, making them a reliable partner for building innovative solutions from the ground up.”
Sudhir Menon
Co-founder & CPO
“Talentica has been part of the family at Mist, and they have been a key part of our engineering team. They bring us startup spirit and a wide range of required skills like Data Science, AI, Cloud, DevOps, UI, and Embedded.”
Bob Friday
Co-founder & CTO
“For an early-stage startup like ours, Talentica understood what we thought about user needs and the problems we were trying to solve. They imbibed our vision and helped us design and build a product that will sell and get to the market successfully. They brought expertise in emerging technologies like artificial intelligence and blockchain to enable innovation for us.”
Carmelle Cadet
Founder & CEO
“With Talentica, you get your engineering solution in one place. You can depend on them as you would depend on a family member. It allows you to be confident that all your engineering team needs will be met and grow in one space as opposed to trying to find them (solutions) with individual services or individual skill sets of people from the outside.”
Luke Jubb
President & COO
DIG DEEPER
Insights from Engineering Data Platforms
Watch Video
Is Your Data Ready for AI? Common Pitfalls and Practical Solutions
Principal Architect
Technologies
Languages & Frameworks
Data Lake & Warehouse Platforms
Data Processing Ecosystem
Database & Storage Engines
Security & Compliance Tools
Operations, Scaling & Monitoring
Load Testing & Benchmarks
FAQs
Timelines depend on scale and complexity, but we have repeatedly delivered production-grade data platforms within phased, milestone-driven engagements.
Security is built into the architecture using secure data handling, automated governance, vulnerability assessments, monitoring, and audit-aligned compliance frameworks, ensuring platforms remain compliant at scale.
Languages & Frameworks
Java, Python, Scala, Spark, Flink, Hadoop ecosystems.
Data Lake & Warehouse Platforms
S3, GCS, SQL Server, BigQuery, Snowflake, Redshift.
Data Processing Ecosystem
Kafka, Spark, Flink, ETL tools, Debezium, Kafka Connect.
Database & Storage Engines
Postgres, SQL Server, Elasticsearch, Cassandra, Redis, graph DBs, time-series DBs.
Security & Compliance Tools
Compliance frameworks, penetration testing, vulnerability tools, secure automation.
Operations, Scaling & Monitoring
Kubernetes (HPA/autoscaling), EC2, Docker, DataOps/MLOps, Prometheus, Grafana, New Relic.
Load Testing & Benchmarks
5 TPC-DS, GridMix3, SparkPerf, Kafka benchmarking tools, BigBench.
Yes. Talentica has extensive experience modernizing legacy data systems and migrating them to cloud-native Lakehouse and warehouse architectures on S3, GCS, and Azure. This includes re-architecting monolithic systems into scalable pipelines, supporting both structured and unstructured data, and enabling real-time and historical analytics without disrupting existing operations