Job Description

Data Engineer

We are looking for a highly skilled Full Stack Data Engineer with expertise in data technologies like snowflake, Azure Data Factory, Databricks to design, develop, and optimize end-to-end data pipelines, data platforms, and analytics solutions. This role combines strong data engineering, cloud platform expertise, and software engineering skills to deliver scalable, production-grade solutions.

Key Responsibilities

• Design and develop ETL/ELT pipelines on platforms like Databricks (PySpark, Delta Lake, SQL), Informatica, Teradata, Snowflake.

• Architect data models (batch and streaming) for analytics, ML, and reporting.

• Optimize performance of large-scale distributed data processing jobs.

• Implement CI/CD pipelines for Databricks workflows using GitHub Actions, Azure DevOps, or similar.

• Build and maintain APIs, dashboards, or applications that consume processed data (full-stack aspect).

• Collaborate with data scientists, analysts, and business stakeholders to deliver solutions.

• Ensure data quality, lineage, governance, and security compliance.

• Deploy solutions across cloud environments (Azure, AWS, or GCP).

Required Skills & Qualifications

Core Databricks Skills:

• Strong in PySpark, Delta Lake, Databricks SQL.

• Experience with Databricks Workflows, Unity Catalog, and Delta Live Tables.

• Experience in snowflake, data engineering technologies like ETL, ELT

Programming & Full Stack:

• Python (mandatory), SQL (expert).

• Exposure to Java/Scala (for Spark jobs).

• Knowledge of APIs, microservices (FastAPI/Flask), or basic front-end (React/Angular) is a plus.

Cloud Platforms:

• Proficiency with at least one: Azure Databricks, AWS Databricks, or GCP Databricks.

• Knowledge of cloud storage (ADLS, S3, GCS), IAM, networking.

DevOps & CI/CD:

• Git, CI/CD tools (GitHub Actions, Azure DevOps, Jenkins).

• Containerization (Docker, Kubernetes is a plus).

Data Engineering Foundations:

• Data modeling (OLTP/OLAP).

• Batch & streaming data processing (Kafka, Event Hub, Kinesis).

• Data governance & compliance (Unity Catalog, Lakehouse security).

Nice-to-Have

• Experience with machine learning pipelines (MLflow, Feature Store).

• Knowledge of data visualization tools (Power BI, Tableau, Looker).

• Exposure to Graph databases (Neo4j) or RAG/LLM pipelines.

• Experience working in Informatica, Teradata in ETL, ELT

Qualifications

• Bachelor’s or Master’s in Computer Science, Data Engineering, or related field.

• 4–7 years of experience in data engineering, with deep expertise in Databricks.

Soft Skills

• Strong problem-solving and analytical skills.

• Ability to work in fusion teams (business + engineering + AI/ML).

• Clear communication and documentation abilities.

About Us

At Codvo, we are committed to building scalable, future-ready data platforms that power business impact. We believe in a culture of innovation, collaboration, and growth, where engineers can experiment, learn, and thrive. Join us to be part of a team that solves complex data challenges with creativity and cutting-edge technology.