Stellarsoft helps organizations design, modernize, and operate reliable cloud data platforms — with hands-on expertise across AWS and Microsoft Azure, paired with hands-on consulting and Power BI-driven analytics to turn that data into decision-ready insight.
Design and build production-grade data platforms on AWS and Azure — ingestion, transformation, storage, orchestration and consumption, built to run reliably.
Layered data platforms built with Amazon S3, Apache Iceberg, AWS Glue Data Catalog, Athena, Spark, and Databricks.
Batch and incremental pipelines for structured and semi-structured data, including complex business transformations and multi-source integration.
Migration of legacy databases, ETL processes and warehouse workloads into modern cloud architectures while preserving business logic, auditability and data integrity.
Change-data-capture and delta-processing patterns for systems that need efficient synchronization rather than repeated full data loads.
Source-to-target reconciliation, duplicate detection and data-quality controls, plus investigation and remediation of failed or underperforming pipelines.
Production workflows built with Apache Airflow and AWS MWAA, including dependency management, retries, parameterization and operational monitoring.
Power BI dashboards and semantic models built on governed data, backed by independent, vendor-neutral advisory on architecture and platform strategy.
Beyond data platforms, we design and build custom software applications on our own technology stack — from internal tools to full product builds, like our upcoming IMS Tracker platform.
Our deepest hands-on experience is in financial services data environments — complex source systems, strict reconciliation requirements, and data that has to be right. The same engineering disciplines apply anywhere data is complex, sensitive, or high-volume:
Drawn from real engineering work in enterprise financial-services environments. Client names are withheld; the engineering challenges and approach are real.
Legacy Data Platform Modernization. Core data processing ran on legacy SQL-based logic that was difficult to scale or maintain. We designed a multi-layer AWS data platform using landing, staging and curated data areas, migrating legacy SQL processing into distributed Spark and AWS Glue pipelines with Apache Iceberg tables — replacing brittle legacy processing with a platform built to scale.
Data Reconciliation & Quality Controls. Data from multiple source systems needed to be trustworthy enough for financial reporting. We implemented source-to-target reconciliation and audit controls and built full and incremental extraction processes — creating a repeatable process for catching data discrepancies before they reached downstream systems.
Enterprise Integration & Orchestration. Data was scattered across multiple operational systems with no standardized model. We integrated it into standardized enterprise data models and designed Airflow workflows for production-grade orchestration — delivering standardized, consistent data to the business systems that depend on it.
Our engineering experience includes enterprise financial-services environments with multiple source systems, large relational data models, complex transformation rules and downstream integrations. Recent work includes:
Stellarsoft can work as an independent delivery team or alongside an existing engineering organization.
Defined deliverables, milestones and budget.
Flexible engineering capacity for evolving requirements.
Ongoing access to senior engineering and implementation capacity.
We are particularly well suited to organizations that: