Senior Data Engineer

Sky Systems, Inc. (SkySys); Argentina; Remote; ARS 184,752,000 - 277,128,000; Full time

Job summary

Sky Systems, Inc. (SkySys) seeks a Senior Data Engineer to design and develop scalable data pipelines for enterprise integrations and analytics.

You will collaborate with Product Owners and cross-functional teams to deliver high-quality solutions aligned with data architecture and governance. Leverage modern cloud technologies such as Snowflake or Databricks, implement Lakehouse and Medallion architectures, and ensure data quality, lineage, and security across the Enterprise Data Warehouse and

Qualifications

• 5–8 years creating quality data pipelines and system integrations.
• Hands-on Databricks and/or Snowflake with Delta Lake.
• Advanced SQL and Python proficiency.
• Experience with streaming/batch processing and ETL/ELT tooling.

Responsibilities

• Design and develop data pipelines and integrations that are performant, scalable, and flexible.
• Lead enterprise-wide data initiatives with cross-functional teams and Product Owners.
• Develop automated testing and deployment scripts for pipelines and integrations.
• Provide database support and address user questions; resolve data issues as part of Tier 3 support.
• Create and maintain data pipeline documentation including data flow and lineage.

Skills

Databricks

Snowflake

Delta Lake

PySpark

SQL

Python

Data Modeling

ETL/ELT

CI/CD

Cloud Platforms

Education

Bachelor’s degree in Computer or Information Science

Tools

Databricks

Snowflake

Airflow

dbt

Job description

Location: Remote

Work hours: US (EST)

About the Role

Our client needs a Senior Data Engineer who can design and develop data pipelines to support system integrations and analytical platforms. They are looking for someone who can lead large-scale, enterprise-wide initiatives while collaborating with Product Owners and cross-functional technical teams. The ideal candidate should be able to deliver scalable, flexible, and high-quality solutions aligned with data architecture and governance strategies, leveraging modern cloud technologies such as Snowflake or Databricks.

Responsibilities include, but are not limited to:

• Design and develop data pipelines and integrations that are performant, scalable, and flexible.
• Work with project teams to deliver system integration pipelines, ensuring a high degree of reliability and resiliency.
• Work with business users and project teams to provide SME guidance, finalize pipeline requirements, and develop level of effort estimates.
• Develop automated testing and deployment scripts to support integrations and pipelines.
• Provide database support by coding utilities, responding to user questions, and resolving problems.
• Create and maintain documentation of data pipelines, including data flow and data lineage documentation.
• Be responsible for Tier 3 support and assist the Operations Team as required to provide a great customer experience for users.
• Be responsible for overall data quality as it relates to the Enterprise Data Warehouse and associated Data Marts. Provide data analysis as required to troubleshoot data issues.
• Assist with integration-related code reviews and mentor junior developers.
• Implement data governance and master data management principles as part of data pipeline development and delivery.

Qualifications

• Lakehouse Architecture: Hands-on experience building Lakehouse solutions on Databricks (Delta Lake, Unity Catalog) or Snowflake (Iceberg Tables, Horizon Catalog).
• Medallion Architecture: Proven ability to design Bronze/Silver/Gold layers for curated, analytics-ready data.
• Streaming or Batch Processing: Experience implementing Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake Dynamic Tables / Snowpipe Streaming.
• Semantic Layer: Experience building and managing semantic models using Databricks AI/BI Genie or Unity Catalog Metrics or Snowflake Semantic Views / Cortex Analyst to enable consistent, governed metrics for BI and AI consumption.
• ETL/ELT Orchestration: Building pipelines with Airflow, Databricks Lakeflow, or Snowflake Openflow; familiarity with dbt is a plus.
• Programming: Strong PySpark or advanced SQL skills; Python for data engineering or automation.
• Data Modeling: Dimensional modeling, Data Vault, or schema design for analytical workloads.
• Performance Tuning: Cluster/warehouse sizing, partitioning, clustering keys, Z-ordering, or query optimization.
• Governance & Security: Working knowledge of Unity Catalog (Databricks) or Horizon Catalog (Snowflake) for lineage, access control, or data quality.
• CI/CD & DevOps: Git, Databricks Asset Bundles or Snowflake CLI/Schemachange, automated testing, or deployment pipelines.
• Cloud Ecosystem: AWS (S3, Glue, Kinesis), Azure, or GCP services supporting modern data platforms.
• AI/ML Enablement: Familiarity with Databricks Mosaic AI or Snowflake Cortex for GenAI or ML use cases.
• Collaboration: Strong communication skills to partner with Product Owners, Analysts, or cross-functional engineering teams.
• Education: Bachelor’s degree in Computer or Information Science or a related field, or an equivalent combination of education and experience.
• Experience: 5–8 years creating quality data pipelines and system integrations, with at least 3 years of experience in a cloud environment.

Must-Have Requirements

• Strong hands-on experience building data pipelines with Databricks, Apache Spark (PySpark), and Delta Lake.
• Advanced SQL and Python, with strong data modeling skills across dimensional and Lakehouse patterns.
• Experience with streaming ingestion using Structured Streaming, Auto Loader, Kafka, or Event Hubs.
• Experience with workflow orchestration (Databricks Workflows, Airflow, or Azure Data Factory).
• Experience with legacy platform migrations, ETL modernization, or managing data hygiene when porting old systems.
• Strong problem-solving, collaboration, and communication skills, including mentoring junior engineers and explaining data concepts to non-technical stakeholders.
• Familiarity with Unity Catalog, data governance, access control, and PII handling.
• Experience with dbt or an equivalent transformation framework.
• Familiarity with secure coding standards and industry security best practices.

Nice-to-Have Requirements

• Experience with Infrastructure as Code (IaC) using Terraform and CI/CD using Azure DevOps.
• Experience working with relational databases, specifically PostgreSQL, and data persistence concepts