Data Platform Engineer

Posted 15 days agoViewed

View full description

💎 Seniority level: Middle, 4+ years

📍 Location: United States

💸 Salary: 130000.0 - 160000.0 USD per year

🔍 Industry: Data & Analytics

🏢 Company: GameChanger

🗣️ Languages: English

⏳ Experience: 4+ years

🪄 Skills: AWSBackend DevelopmentDockerPythonSoftware DevelopmentSQLETLGitKafkaSnowflakeAirflowData engineeringCI/CDTerraform

Requirements:

4+ years of experience in software development as a data or backend engineer.
Proficiency in Python and SQL for processing data.
Experience with some of the following technologies (or similar tools): Airflow, Docker, Kafka, AWS, Terraform, Snowflake, Git version control / GHA cicd
Stay informed about relevant technology trends and developments and contribute to technical design discussions.
Enjoy working with others and collaborating to solve problems efficiently.

Responsibilities:

Develop and maintain scalable and efficient data pipelines to support analytics needs across the organization, with a focus on dynamic and generalized solutions.
Improve the performance, observability, and reliability of existing data systems including our orchestrator and our custom ETL service.
Collaborate with other teams to understand data needs and implement solutions that improve efficiency.
Ensure system security and data privacy compliance.
Participate in code reviews, technical documentation, and knowledge-sharing initiatives.

Apply

Related Jobs

Apply

🔥 Sr. Data Platform Engineer - GenAI Apps

Posted about 1 month ago

📍 United States

🧭 Full-Time

💸 140000.0 - 190000.0 USD per year

🔍 Healthcare

🏢 Company: Qventus👥 101-250💰 $85,000,000 Series D 3 months agoArtificial Intelligence (AI)Machine Learning Hospital Analytics Health Care

🔧 Requirements

Excellence in quality data pipeline design, development, and optimization to create reliable, modular, secure data foundations for the organization's data delivery system from applications to analytics & ML
Expertise in Python, SQL, and familiarity with AWS tools, Databricks, and DBT.
Strong understanding of database structure systems and data mining.
Innate aptitude for interpreting complex datasets with demonstrated ability to discern underlying patterns, identify anomalies, and extract meaningful insights, demonstrating advanced data intuition and analytical skills.
Proven ability to independently handle ambiguous project requirements and lead data initiatives from start to finish, while collaborating extensively with cross-functional, non-technical teams to inform and shape product development.

💡 Responsibilities

Lead the design, development, and management across investments to platform, model infrastructure, and data pipelines in support of data intensive AI solutions.
Work closely with a close knit team of solution experts & innovators to design, iterate, and develop key pipelines to unlock new solution functionality, analytical insights, and machine learning features.
Identify, monitor, and lead initiatives to ensure our data platform remains scalable, reliable, and efficient in light of evolving data requirements of our products and services - particularly in the rapidly changing Gen AI / LLM ecosystem
Partner with cross-functional stakeholders & peers to translate data needs into technical solutions with rigorous technical scope to enable more junior engineers
Spearhead the discovery, evaluation, and integration of new datasets, collaborating (incl. pipeline development and data modeling/documentation), working closely with key data stakeholders to understand their impact and relevance to our core products and the healthcare domain.
Translate product / analytical vision into highly functional data pipelines supporting high quality & highly trusted data products (incl. designing data structures, building and scheduling data transformation pipelines, improving transparency etc.).
Engage in the rapid new AI product development from concept to deployment, ensuring robust platform supporting easy iteration and monitoring.
Set the standard for data engineering practices within the company, guiding the architectural approaches, data pipeline designs, and the integration of cutting-edge technologies to foster a culture of innovation and continuous improvement.

AWSPythonSQLAgileETLKubernetesMachine LearningData engineeringREST APICommunication SkillsAnalytical SkillsCI/CDProblem SolvingData visualizationData modelingData analytics

Posted about 1 month ago

Apply

🔥 Senior Data Platform Engineer

Posted about 1 month ago

📍 United States

🧭 Full-Time

💸 150000.0 - 185000.0 USD per year

🔍 Healthcare

🏢 Company: Qventus👥 101-250💰 $85,000,000 Series D 3 months agoArtificial Intelligence (AI)Machine Learning Hospital Analytics Health Care

🔧 Requirements

3+ years of experience designing, building, and operating cloud-based, highly available, observable, and scalable data platforms utilizing large, diverse data sets in production to meet ambiguous business needs
Strong cross-functional communication - ability to break down complex technical components for technical and non-technical partners alike
Experience working with Data Science teams to support ML Ops

💡 Responsibilities

Lead scoping and execution of critical improvements to our data platform to maintain overall system health and improve data observability in lieu of changing product needs and to optimize innovation velocity
Provide expertise on the overall data engineering best practices, standards, architectural approaches and complex technical resolutions
When needed support solution development; translate product / analytical vision into highly functional data pipelines supporting high quality & highly trusted data products (incl. designing data structures, building and scheduling data transformation pipelines, improving transparency etc.)

AWSDockerLeadershipPythonSQLApache AirflowBashCloud ComputingData AnalysisETLKubernetesMachine LearningMicrosoft AzureMLFlowSnowflakeCross-functional Team LeadershipAlgorithmsData engineeringData scienceData StructuresPostgresREST APISparkCommunication SkillsAnalytical SkillsCI/CDProblem SolvingMentoringTerraformMicroservicesData visualizationData modeling

Posted about 1 month ago

Apply

🔥 Data Platform Engineer I

Posted 2 months ago

📍 Kenya, Philippines, Mexico, India, United States

🔍 Financial Services

🔧 Requirements

The role requires excellent communication skills.
Candidates should be able to collaborate with internal clients effectively.
Knowledge and experience related to data platforms are necessary.

💡 Responsibilities

The Data Platform Engineering team is building the infrastructure to support a best-in-class decision engine.
The role requires excellent communication to collaborate with key partners - Machine Learning Engineers, Data Scientists, and Analytics Engineers.
The team serves internal clients by setting up, maintaining, and evolving infrastructure and tooling.
The team advises backend and frontend teams on adopting the Event-Driven Data Mesh paradigm.

AWSPostgreSQLPythonETLKafkaData engineering

Posted 2 months ago

Apply

🔥 Data Platform Engineer

Posted 3 months ago

📍 United States

🔍 Advanced analytics consulting

🏢 Company: Tiger Analytics👥 1001-5000 Advertising Consulting Big Data News Machine Learning Analytics

🔧 Requirements

Proven experience designing and implementing scalable, high-performance data systems in cloud environments.
Advanced knowledge of real-time data streaming platforms such as Apache Kafka and AWS Kinesis.
Expertise in working with AWS for cloud-based data solutions.
Proficiency in Databricks for big data processing and managing data pipelines.
Strong hands-on experience with Scala and Java for developing data-intensive applications.
Familiarity with Apache Spark for distributed data processing.
Experience with Kubernetes or other orchestration frameworks.
Experience writing infrastructure as code.

💡 Responsibilities

Lead the solution design and implementation of end-to-end data pipelines that support real-time streaming and integration across multiple platforms.
Manage and mentor a team of engineers, providing guidance on technical approaches and troubleshooting.
Drive modernization efforts for existing data platforms with cloud-native technologies.
Design and implement robust streaming data pipelines using technologies like Apache Kafka and Kinesis.
Identify bottlenecks in data workflows to improve performance and increase throughput.
Ensure reliability and resilience of the data platform, focusing on monitoring and incident management.
Advise and enforce best practices for data management processes and data quality.
Collaborate with cross-functional teams to deliver business value.

AWSCloud ComputingJavaKubernetesApache KafkaData engineeringScala

Posted 3 months ago

Apply