Data Architect (AWS)

SoftServe; Poland; On-site; PLN 180,000 - 270,000; Full time

Job summary

SoftServe is seeking a data engineering specialist to design and implement scalable data platforms in AWS. You will work on batch and streaming pipelines, collaborating with technical and business stakeholders to deliver end-to-end solutions.

You will leverage Python/SQL, Spark, and modern data warehousing tools to build robust data architectures, while contributing to architecture discussions and knowledge sharing within the team.

Qualifications

• Proven experience designing scalable data platforms and data pipeline architectures.
• Hands-on experience with batch and streaming data processing solutions.
• Strong expertise in AWS cloud services for data engineering and analytics workloads.
• Proficiency in Python, SQL, and at least one JVM language (Java/Scala).
• Knowledge of big data technologies such as Spark, Databricks, or Flink.
• Experience with orchestration tools (Airflow/MWAA).
• Experience with streaming (Kafka/MSK/Kinesis) and data warehousing (Snowflake/Redshift).
• Upper-intermediate or higher level of English.

Responsibilities

• Design and implement scalable data pipelines using AWS services.
• Develop batch and streaming data processing architectures.
• Collaborate with stakeholders to translate requirements into technical solutions and plans.
• Support data ingestion and source-to-target mappings for new data sources.
• Participate in architecture discussions to scale the data platform and data models.
• Work with Airflow/MWAA to manage workflows.
• Support real-time processing with Kafka, MSK, or Kinesis.

Skills

AWS

Python

SQL

Data Engineering

Batch & streaming

Stakeholder communication

Tools

Airflow

MWAA

Kafka

MSK

Kinesis

Snowflake

Redshift

Databricks

Spark

Flink

Job description

About The Role

In this role, you will contribute to designing and implementing scalable data platforms and data processing solutions within AWS environments. You will work with both batch and streaming architectures, collaborate with technical and business stakeholders, and support delivery activities across the full project lifecycle in a collaborative and innovation-driven engineering environment.

About The Role

In this role, you will contribute to designing and implementing scalable data platforms and data processing solutions within AWS environments. You will work with both batch and streaming architectures, collaborate with technical and business stakeholders, and support delivery activities across the full project lifecycle in a collaborative and innovation-driven engineering environment.

Responsibilities

• Design and support the implementation of scalable data solutions and data pipelines using AWS services
• Develop and maintain batch and streaming data processing architectures
• Collaborate with stakeholders to gather requirements and translate them into technical solutions and implementation plans
• Support data ingestion activities, including source-to-target mappings and integration of new data sources
• Participate in architecture discussions and contribute to scaling the data platform and maintaining data models
• Work with orchestration tools such as Apache Airflow or MWAA to manage workflows
• Support implementation of real-time data processing solutions using Apache Kafka, Amazon MSK, or Kinesis
• Utilize data warehousing solutions such as Snowflake or Amazon Redshift for analytics and storage
• Create and maintain technical documentation, data schemas, and solution-related materials
• Participate in the full project lifecycle, from PoC and MVP stages to production implementation
• Explore new technologies, build prototypes, and contribute to knowledge sharing within the engineering community

Requirements

• Proven experience designing scalable data platforms and data pipeline architectures
• Hands-on experience with batch and streaming data processing solutions
• Strong expertise in AWS cloud services for data engineering and analytics workloads
• Proficiency in Python, Scala, or Java (preferably Python), along with strong SQL skills
• Knowledge of big data technologies such as Apache Spark, Databricks, or Flink
• Experience with orchestration tools such as Apache Airflow or MWAA
• Practical experience with streaming technologies such as Apache Kafka, Amazon MSK, or Kinesis
• Familiarity with data warehousing solutions such as Snowflake or Amazon Redshift
• Upper-intermediate or higher level of English

SoftServe is an equal opportunity employer. Qualified applicants will receive consideration regardless of race, color, ancestry, ethnicity, national origin, religion, sex, sexual orientation, gender identity or expression, age, citizenship, disability, health condition, marital or family status, veteran status, or any other characteristic protected by applicable law.