Sinch is looking for a talented and experienced Senior Data Engineer to join our Data Engineering team. In this crucial role, you will be responsible for building, maintaining, and supporting data pipelines that connect our various products globally. You will use innovative approaches and technologies, designing data architectures that empower the data domain and provide actionable insights that support key decisions across the organization.
Sinch is a global customer engagement platform that provides communication services for businesses across messaging, voice, and email. Sinch's services are used by more than 150,000 businesses, including many of the world's largest tech companies.Responsibilities
Design and implementrobust, scalable data pipelinesthat ensure data accuracy and availability across multiple platforms.
Work on thedata integrationof various Sinch platforms and products worldwide.
Contribute to data pipelines development, performance, quality, monitoring, and maintenance.
Optimizeexisting data workflows and databases for performance and scalability, using best practices and cutting-edge tools.
Identify opportunities for improvement in our products, business, and architecture through the strategic use of data.
Lead data engineering projects, serving as atechnical referenceand providing guidance to team members (e.g., through code reviews).
Collaborate actively with data scientists, analysts, and product teams to understand data needs and deliver high-quality solutions.
Advocate forData Engineering best practicesboth inside and outside the team.
Stay abreast of emerging technologies and industry trends to contribute innovative ideas to our data strategy.Must Have
Consistent experienceas a Data Engineer or in a related role.
Strong knowledge ofsoftware development(e.g.,Python, Spark, Git, CI/CD, Docker).
Expertise inSQLto query data and buildETL/ELTprocesses.
Proficiency in designing modern data pipelines and architectures.
Experience working withData Lake and Data Warehouseconcepts, using best practices to structure and store big volumes of data.
Ability totroubleshoot and optimizedata pipelines for performance and reliability.
Experience in data pipeline creation/orchestration tools (e.g.,Airflow ,Dagster ).
Hands-on knowledge of cloud environments (e.g.,AWSorGCP ).
Experience usingDatabricksor database technologies such asSnowflakeorDelta Lake .
Knowledge of different data architectures (e.g., Data Lake, Data Mesh, Data Fabric).
Fluent Englishfor effective communication with technical and business stakeholders.
Demonstrated ability to collaborate effectively andcommunicate complex ideas clearly .Nice to Have
Experience withreal-time data processingand related tools/frameworks.
Experience designing and implementing new data architectures.
Experience using anydata governance/management tool .
Experience using a tool (e.g.,Dremio ) to create avirtualization layer .
Knowledge of data security best practices (encryption, access controls).
Ability to organize and break down complex projects/initiatives into manageable tasks.Desired Skills and Experience
Consistent experience as a Data Engineer or in a related role.
Strong knowledge of software development (e.g., Python, Spark, Git, CI/CD, Docker).
Expertise in SQL to query data and build ETL/ELT processes.
Proficiency in designing modern data pipelines and architectures.
Experience working with Data Lake and Data Warehouse concepts, using best practices to structure and store big volumes of data.
Ability to troubleshoot and optimize data pipelines for performance and reliability.
Experience in data pipeline creation/orchestration tools (e.g., Airflow, Dagster).
Hands-on knowledge of cloud environments (e.g., AWS or GCP).
Experience using Databricks or database technologies such as Snowflake or Delta Lake.
Knowledge of different data architectures (e.g., Data Lake, Data Mesh, Data Fabric).
Fluent English for effective communication with technical and business stakeholders.
Demonstrated ability to collaborate effectively and communicate complex ideas clearly.