Cloud Data Engineer

We are looking for an experienced Developer with strong skills in AWS DevOps Python AWS Glue and Apache Spark working on day shifts without travel requirements. The professional will design build and optimize data pipelines and cloud applications that support large scale analytics initiatives for an international organization improving reliability performance and security across key business platforms.

Requirements:

• Experience: 4 - 8 years

• Spanish language proficiency is mandatory.

• Technical Skills: AWS DevOps Python AWS Glue Apache Spark Domain Skills T

• Technology : Cloud Modernization/Migration. (Nice to have)

Responsibilities:

• Design scalable cloud based data solutions using AWS services that transform complex business requirements into efficient and maintainable applications that improve analytics capabilities for global stakeholders

• Develop robust Python based components including data processing scripts reusable libraries and automation utilities that enhance productivity and reduce manual operational effort -Build and optimize AWS Glue jobs to handle large volume data ingestion transformation and loading with a strong focus on reliability performance tuning and error handling to support mission critical reporting

• Implement Apache Spark applications for batch and near real time data processing ensuring efficient resource utilization and consistent data quality across multiple environments

• Apply AWS DevOps practices by configuring continuous integration and continuous delivery pipelines that streamline code deployment reduce release risk and support frequent delivery of high quality features

• Manage infrastructure as code using appropriate AWS tools by defining repeatable templates that enable consistent environment provisioning configuration and scaling across development testing and production

• Monitor application and pipeline performance with cloud native observability tools and implement proactive alerting mechanisms that reduce incident resolution time and improve system availability

• Collaborate closely with data engineers analysts and product teams to translate analytical needs into reliable technical solutions that support business decision making and long-term data strategy.

• Ensure strong security and compliance controls in all solutions by applying identity management network protection and data governance practices aligned with enterprise and regulatory standards

• Conduct code reviews share best practices and refine development guidelines that promote clean readable and testable code while fostering a culture of continuous improvement within the technical team

• Create clear technical documentation including architecture overviews runbooks and operational guides that support knowledge sharing smooth onboarding and efficient incident handling -Participate in backlog refinement and sprint activities by estimating tasks identifying dependencies and providing status updates that keep delivery plans predictable and aligned with stakeholder expectations

• Drive continuous optimization of data workflows by identifying bottlenecks experimenting with configuration changes and implementing targeted improvements that reduce processing time and operational costs

Qualifications:

• CLOUD ENVIRONMENTS: Experience developing data systems on major cloud platforms (AWS, GCP, Azure).

• DATA ARCHITECTURE: Hands-on experience building modern data architectures, including data lakes, data lakehouses, and data hubs, along with related capabilities such as ingestion, governance, modeling, and observability.

• DATA INGESTION: Demonstrated proficiency in data collection, ingestion tools (Kafka, AWS Glue), and storage formats (Iceberg, Parquet).

• DATA STREAMING: Experience developing data pipelines with streaming architectures and tools (Kafka, Flink).

• DATA MODELING: Expertise in data transformation and modeling using SQL-based frameworks and orchestration tools (dbt, AWS Glue, Airflow). Deep experience with modeling concepts like SCD and schema evolution.

• DATA TRANSFORMATION: Strong background with using Spark for data transformation, including streaming, performance tuning, and debugging with Spark UI.

• PROGRAMMING: Advanced programming skills in Python, Java, Scala, or similar languages. Expert-level proficiency in SQL for data manipulation and optimization.

• DEVOPS: Demonstrated experience in DevOps practices, including code management, CI/CD, and deployment strategies.

• DATA GOVERNANCE: Strong background in data governance principles, including data quality, privacy, and security considerations for data product developer.

Work model: Hybrid

We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a hybrid position requiring 2 days a week in a client or Cognizant office in São Paulo - SP. Regardless of your working arrangement, we are here to support a healthy work-life balance though our various wellbeing programs.

Please, upload your resume in English.

Job Location: BRSPSAOA04(ITBRA Sao Paulo SP - Rua Jaceru-COG

Certifications Required: Preferred certifications include AWS Certified Developer Associate or AWS Certified DevOps Engineer and any recognized Python programming certification.