Location: Remote
Department: Data & Analytics
Employment Type: Full-Time
About the Role:
Modern Solutions helps clients design, build, and scale cloud-native data platforms that power business transformation. We work across industries to unify complex data sources, enable real-time analytics, and leverage AI and machine learning to deliver measurable business impact.
We are seeking a Senior Data Engineer with proven leadership experience to guide a cross-functional team of data engineers, scientists, and DevOps specialists. This role will focus on architecting and implementing scalable data solutions that support analytics, AI, and customer-facing digital experiences.
Key Responsibilities:
- Lead & Mentor: Guide a team of data engineers, data scientists, and DevOps professionals; establish best practices and ensure delivery quality.
- Data Architecture: Design and maintain modern, scalable data architectures integrating multiple structured and unstructured data sources.
- ETL & Streaming: Build robust pipelines using Kafka (or equivalent), Spark, Airflow, or dbt to support both batch and real-time ingestion.
- Cloud Platforms: Develop across AWS, GCP, and Azure with hands-on expertise in Snowflake, Databricks, and BigQuery.
- AI/ML Enablement:
- Build and optimize feature pipelines for AI/ML models.
- Support deployment, monitoring, and retraining workflows for ML models.
- Collaborate with data science teams to make production-grade models scalable and reliable.
- APIs & Integrations: Architect secure, performant APIs for system-to-system data sharing and real-time inference.
- Analytics & BI: Enable self-service analytics in Power BI, Looker Studio, or Tableau, ensuring governed, high-quality data.
- Digital Analytics & Marketing Data:
- Integrate and normalize data from GA4, Adobe Analytics, GTM, and server-side tracking frameworks.
- Build data pipelines from Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads, DV360 and other paid media sources.
- Ingest social listening and customer feedback platforms (Sprinklr, Brandwatch, Talkwalker, Birdeye) into the data ecosystem.
- Ensure end-to-end visibility across marketing, web, and customer data for attribution and optimization.
- Governance & Security: Implement data governance, lineage, and compliance practices aligned with SOC2, ISO27001, GDPR, and industry standards.
What We’re Looking For:
- 5+ years of experience in data engineering, with at least 2 years in a senior/lead capacity.
- Strong experience in building and managing data pipelines (batch + streaming).
- Hands-on expertise in Kafka, Spark, or equivalent ETL tools.
- Advanced skills in SQL and exposure to NoSQL databases (MongoDB, DynamoDB, Cassandra).
- Proficiency with at least one major cloud provider (AWS, GCP, Azure).
- Experience with modern data platforms: Databricks, Snowflake, BigQuery.
- Solid programming background in Python, Scala, or Java.
- Familiarity with containerization and CI/CD (Docker, Kubernetes, Terraform, GitHub/GitLab pipelines).
- Experience in operationalizing AI/ML models and working with feature stores.
- Working knowledge of digital analytics (GA4, Adobe Analytics) and experience integrating marketing/ad tech data sources into data warehouses.
- Strong communication skills with ability to bridge technical detail and business impact.
Preferred Skills:
- Experience in multi-brand, high-scale environments with millions of data events per day.
- Familiarity with customer 360 initiatives, journey orchestration, and personalization use cases.
- Knowledge of AI-driven data quality, anomaly detection, and predictive analytics.
- Understanding of attribution models, campaign optimization, and martech ecosystems.
What We Offer
- Opportunity to lead data engineering within AI-enabled, analytics-rich transformation projects.
- Dynamic, cross-disciplinary environment across industries and cloud ecosystems.
- Competitive salary and benefits.
- Hybrid/flexible working culture.