Job Description
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Big Data Tech Lead in the European Union.
As a Big Data Tech Lead, you will guide and oversee data-driven projects that transform business insights into actionable strategies. You will manage and mentor engineering teams, design scalable data architectures, and ensure the successful delivery of complex analytics solutions. This role offers the opportunity to work with cutting-edge AWS cloud services, advanced data processing frameworks, and a variety of industries, from IoT and ML/AI to enterprise analytics. You will balance technical leadership with hands-on contribution, shaping both the technology and strategic direction of high-impact projects in a fully remote environment.
Accountabilities:
- Assist in the technological supervision of projects, including code reviews, resolving technical challenges, and clarifying business requirements.
- Support pre-sales efforts by providing technical input for scope estimation and LOE assessments.
- Define and prioritize project requirements from vague or high-level specifications, ensuring alignment with business impact.
- Plan, manage, and execute the technical aspects of projects, maintaining high quality and adherence to best practices.
- Operate in the customer’s best interest, delivering knowledge confidently and fostering collaboration during incident responses.
- Mentor and guide junior engineers, encouraging best practices and continuous learning.
Requirements
- 1+ year of experience in technological supervision or mentoring (1–2 engineers).
- 3+ years of experience writing analytical SQL queries.
- 1+ year hands-on experience with AWS Data Analytics services (EMR, Glue, Athena, Redshift, etc.).
- 3+ years of Java, Scala, or Python development for data-related projects.
- 1+ year of experience with Hadoop or Spark.
- English proficiency B2 or higher, spoken and written.
- Nice-to-have skills: experience in pre-sales technical estimation, orchestration frameworks (Airflow, Step Functions), streaming analytics (Kinesis, Kafka, Flink, Spark Streaming), CDC/Delta Lakes, and Infrastructure as Code (AWS CDK, Terraform, CloudFormation).
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