CORE SERVICES

Data Engineering · Cloud Data Platforms · Analytics & Consulting

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.

CORE CAPABILITIES

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Cloud Data Platform Engineering

Design and implementation of production data platforms across AWS and other cloud environments, including ingestion, transformation, storage, orchestration, observability, and consumption layers.

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Data Lake & Lakehouse Architecture

Layered data platforms built with Amazon S3, Apache Iceberg, AWS Glue Data Catalog, Athena, Spark, and Databricks.

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ETL / ELT & Data Pipelines

Batch and incremental pipelines for structured and semi-structured data, including complex business transformations and multi-source integration.

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Data Migration & Modernization

Migration of legacy databases, ETL processes and warehouse workloads into modern cloud architectures while preserving business logic, auditability and data integrity.

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CDC & Incremental Processing

Change-data-capture and delta-processing patterns for systems that need efficient synchronization rather than repeated full data loads.

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Data Quality & Reconciliation

Controls for source-to-target completeness, duplicate detection, reconciliation, batch tracking, data-quality rules and operational troubleshooting.

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Workflow Orchestration

Production workflows built with Apache Airflow and AWS MWAA, including dependency management, retries, parameterization and operational monitoring.

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Data Platform Reliability & Optimization

Investigation and remediation of failed pipelines, performance bottlenecks, Spark issues, data inconsistencies, duplicate processing and operational weaknesses.

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Analytics, Dashboards & BI

Turning raw, governed data into decision-ready insight through Power BI dashboards, semantic models, and reporting layers built on top of reliable data platforms.

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Data Architecture & Technical Leadership

Architecture assessment, platform design, technology selection, migration planning and technical guidance for internal engineering teams.

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Data Strategy & Advisory Consulting

Independent, vendor-neutral advisory on data architecture, platform strategy, and technology selection — delivered as standalone consulting engagements or embedded alongside your team.

TECHNOLOGY EXPERTISE

Cloud

AWSAzure

AWS Data Stack

AWS GlueAmazon S3AthenaMWAAGlue Data CatalogRedshiftCloudWatchDMSEMR

Data Processing

Apache SparkApache FlinkPySparkDatabricksPandas

Lakehouse & Warehousing

Apache IcebergSnowflakeRedshiftDelta-based architectures

Orchestration & Transformation

Apache AirflowMWAAdbt

Streaming & CDC

KafkaDebeziumAWS DMSIncremental / delta-processing

Engineering

PythonSQLJava

Databases

PostgreSQLOracleMicrosoft SQL ServerTeradataDynamoDB

Infrastructure & Delivery

TerraformGitAzure DevOpsCI/CD

BI & Analytics

Power BIDAXData Visualization

TYPICAL ENGAGEMENTS

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Data Platform Assessment

Review an existing data environment, identify architectural and operational weaknesses, and provide a prioritized modernization roadmap.

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Cloud Data Platform Implementation

Design and build a complete cloud data platform, from source ingestion through curated datasets and downstream consumption.

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Legacy Data Modernization

Migrate existing databases, ETL processes and business logic into scalable cloud-native data architectures.

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Pipeline Reliability Sprint

Diagnose and resolve failures, performance problems, reconciliation issues and data-quality problems in an existing platform.

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Dedicated Data Engineering Pod

A small engineering team integrated into your delivery organization for ongoing development, migration and platform modernization.

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Analytics & Dashboard Delivery

Design and build Power BI dashboards and semantic models on top of an existing or newly built data platform.

RELEVANT DELIVERY EXPERIENCE

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:

  • Designing multi-layer AWS data platforms using landing, staging and curated data areas
  • Building Spark and AWS Glue pipelines for enterprise datasets
  • Implementing Apache Iceberg tables through AWS Glue Data Catalog
  • Developing full and incremental extraction processes
  • Managing batch-based data processing and metadata tracking
  • Implementing source-to-target reconciliation and audit controls
  • Migrating complex legacy SQL processing into distributed data pipelines
  • Building downstream CRM data extracts
  • Designing Airflow workflows for production data processing
  • Investigating duplicate records, merge conflicts and data-quality issues
  • Integrating data from multiple operational systems into standardized enterprise models

HOW WE WORK

Stellarsoft can work as an independent delivery team or alongside an existing engineering organization.

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Fixed-Scope Project

Defined deliverables, milestones and budget.

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Time & Materials

Flexible engineering capacity for evolving requirements.

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Dedicated Data Engineering Pod

Ongoing access to senior engineering and implementation capacity.

BEST FIT

We are particularly well suited to organizations that:

  • Operate complex AWS or Azure data environments
  • Need to modernize legacy ETL or warehouse systems
  • Are experiencing reliability or data-quality problems
  • Need Spark, Airflow, Glue or Iceberg expertise
  • Are implementing a lakehouse architecture
  • Need CDC or incremental data integration
  • Require experienced engineers without expanding permanent headcount
  • Are preparing their data infrastructure for analytics, machine learning or AI workloads
  • Need dashboards or self-serve BI on top of your data platform

READY TO GET STARTED?