Intro

At Adsquare, our mission is driven by our core focus:

Passion – Solving complex challenges with great people, tech, and data.

Niche– Location Intelligence for Programmatic Advertisers.

Our core values are integral to everything we do:

• Drive: We turn ambition into action.
• Resilience: We adapt, persevere, and grow stronger.
• No BS: We value honesty, transparency, and clear communication.
• Humble: We choose modesty over vanity and let results speak for themselves.
• Moral Compass: We do the right thing with fairness, integrity, and respect.

We seek candidates who not only bring top-tier technical expertise but also embody these values in every aspect of their work.

Your tasks

About the team

As a Senior Engineer, you will be a key contributor in our Data In squad. You will create and maintain scalable big data pipelines and products that power our applications and drive business value. While your primary focus is on developing big data applications and pipelines, you will also leverage some backend services and data analytics when needed.

Reporting Structure:

• You will join a dedicated team of 4, making you the 5th team member.
• You will work under the guidance of a Team Lead in Data Engineering.

Your Mission

• Data Asset Ownership: Be accountable for developing and maintaining data pipelines and data solutions built on large volumes of location signals, geographical (places) data, and audience attribute data, according to defined SLAs and to time and budget.

• Pipeline Development & Deployment:

  Design, develop and deploy robust data transformation pipelines using the latest data engineering technology.

• Technical Leadership & Mentorship:

  Lead and mentor junior team members, sharing your expertise and best practices in data engineering and software development.

• Innovative Data Solutions:

  Conduct R&D to keep Adsquare at the forefront of data innovation in adtech. Develop reliable and maintainable code.

• Data Monitoring & Dashboards:

  Create live monitoring dashboards to support product development and strategic decision-making, ensuring data solutions are properly monitored and maintained.

• Collaboration & Continuous Improvement:

  Communicate with stakeholders, work closely with cross-functional teams to refine and enhance data solutions, always balancing cost efficiency and high-value output.

Your profile

Your Profile

Experience & Technical Expertise:

• Experience: 4 to 6 years as Backend Developer and/or Data Engineer or similar relevant experience.
• Technical Skills:
• Necessary requirements:
• Advanced knowledge of the programming languages Python, Scala, Java and SQL
• understand functional programming principles to create reliable and maintainable data applications
• Work with large-scale data processing frameworks such as Apache Spark
• Expertise in file formats like parquet, hdfs, iceberg
• Design and operate both relational (SQL) and non-relational (NoSQL) databases, applying the right technology in the right context
• Experience handling large datasets(from 100s of GBs to many TB) including tabular, geo-spatial, and behavioral data.
• Familiarity with big data technologies and data warehouses in aws like Athena, EMR, Glue, Redshift, s3, data lake
• Solid foundation in computer science principles including data structures, algorithms and design pattern
• Nice to have:
• experience in Kafka and Flink
• Experience with orchestration tools like Airflow and Step Functions
• Experience with deploying infrastructure via Terraform and Kubernetes
• Degree or PhD in computer science or similar subject like Mathematics, Physics or Engineering

Soft Skills & Personal Attributes:

• Communication: Excellent written and verbal communication skills with an ability to simplify complex technical information.
• Teamwork & Leadership: Experience guiding and mentoring junior team members in a collaborative environment.
• Problem-Solving: A proactive approach to troubleshooting, backed by thorough research and data-driven decision-making.
• Adaptability: the interest and willingness to keep up to date in the field of data engineering and actively adopt new technologies

Methodologies:

• Familiarity with agile methodologies, software design principles (including 12-factor app), and a commitment to best practices in software engineering.