Senior Data Engineer
AI summary
Paystack is hiring a Senior Data Engineer to build and maintain scalable data platforms, pipelines, and infrastructure in a remote-first environment. The role covers data ingestion, processing, storage, streaming, workflow orchestration, CI/CD, and cross-functional collaboration with data scientists and analysts. Candidates need strong Python skills, data pipeline experience, and familiarity with cloud and streaming technologies.
- Remote-first role with cross-functional collaboration across data teams
- Focus on building scalable data pipelines, platforms, and infrastructure
- Requires strong Python skills and data engineering experience
- Involves streaming technologies such as Kafka, Debezium, and Kafka Connect
- Includes on-call rotation for production monitoring and support
AI job guide
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AI salary guide
Not enough public dataNot enough public salary data is available for this exact role. Before applying, prepare to ask about gross pay, benefits, contract length, probation period, transport and any allowances.
Can you qualify for this role?
- Required3+ years of relevant experienceThe job post includes a minimum experience signal.
- RequiredEducation or certification mentioned in the postThe captured text mentions education, a diploma, certificate, or licence.
- PreferredPractical evidence in factory, part_time, entregadorThe tags and summary point to skills connected with this role.
- RequiredAvailability to work in Not specifiedThe vacancy is associated with this location.
Documents to prepare
- Likely requiredUpdated CV
- Role specificCover letter or short employer message
- OptionalProfessional references
- Role specificAcademic or professional certificates
- VerifyID or passport only after verifying the employer
Application tips for this job
- Place your strongest Senior Data Engineer evidence in the first half of your CV.
- In your cover letter or employer message, connect your experience to Paystack and the role in Not specified.
- Add concrete examples related to factory, part_time, entregador, ideally with measurable outcomes or clear responsibilities.
- Follow the instructions from Jobzilla Nigeria; avoid sending documents to unofficial contacts or copied links.
- Confirm the deadline, interview location and employer contact before sharing personal documents.
- Prepare a polite question about pay, benefits and contract terms for later interview stages.
Source and safety check
- Jobzilla Nigeria
- Original source link available
- Application method is clear
- Deadline not specified
- No major risk signal was detected in the captured text.
Never pay for interviews, shortlisting, medical checks, uniforms, or job placement. Confirm every application at the original source before sharing personal documents. Report suspicious listing.
Interview preparation
- What experience makes you a strong fit for this Senior Data Engineer role in factory, part_time?
- How have you handled responsibilities similar to those in this job post?
- Are you available to work in Not specified under the listed contract or schedule?
- Prepare examples with clear responsibilities, tools used and measurable outcomes.
- Review the source and research Paystack before the interview.
Ask what the first priorities will be in the role and how success will be measured.
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Original source description
This involves data ingestion, processing, storage and egress. Data engineers are also responsible for creating and maintaining the infrastructure our data platforms run on. The role requires a proactive individual who can work independently and collaboratively within a remote-first environment, has a strong software engineering background with good experience: building and maintaining data pipelines, expertise in Python and experience: in streaming technologies. Data engineers operate across a diverse tech stack. They are expected to be adaptable and drawn to learning new skills and technologies. Data engineering at Paystack focuses on building and extending platforms for managing data at scale. We’ll trust you to Collaboration: Engage with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data needs and deliver solutions. Database Management: Work with a variety of database technologies, including relational databases (MySQL, PostgreSQL), NoSQL databases (MongoDB) and analytical/big data systems (Redshift, BigQuery, SingleStore). CI/CD Implementation: Develop and maintain continuous integration and deployment pipelines to streamline development processes. Workflow Orchestration: Build, schedule and maintain custom workflows using Apache Airflow to ensure timely and accurate data processing and delivery. Testing and Quality Assurance: Conduct unit and integration testing to ensure high code quality, data integrity and system reliability. Streaming Data Processing: Implement and manage real-time data streaming solutions utilising Kafka, Debezium, Kafka Connect. Monitoring and Support: Monitoring system performance and addressing faults and failures in production systems as part of an on-call rotation. Documentation: Maintain clear and comprehensive documentation of data processes, workflows and systems. Infrastructure as Code: Employ tools like Terraform, Kubernetes, and Helm to manage and provision infrastructure efficiently. Data Pipeline Development: Design, develop, and maintain robust data pipelines using ETL and ELT methodologies to process and integrate data from various sources into a data lake, a central data warehouse, operational data stores, analytical data marts and various application interfaces. You’ll thrive in this role if you have Bachelor's Degree in Computer Science, Engineering or a related field. Experience: in setting up and maintaining CI/CD pipelines. Exposure to analytical systems and basic data science tooling. Familiarity with basic machine learning and analytical modelling concepts advantageous. Experience: with Terraform, Kubernetes, and Helm for infrastructure management. Proficiency in a data pipeline orchestration tool or suitable workflow orchestration tool like Apache Airflow (preferred), Databricks, Dagster or Airbyte. Minimum of 3 years of experience: in data engineering roles, with a focus on building and managing data pipelines. Strong understanding and hands-on experience: working with various database technologies, including MySQL, PostgreSQL, MongoDB and Redshift (BigQuery and SingleStore advantageous) Familiarity with unit and integration testing methodologies. Solid knowledge of cloud computing concepts, with experience: in AWS services being advantageous. Exposure to self-service reporting tools like Tableau, Looker and DOMO. Hands-on experience: with Kafka, Debezium, and Kafka Connect. Proficiency in Python is essential. JavaScript and Scala development experience: is advantageous. Ability to write complex SQL queries across different dialects. Minimum of 2 years experience: in software and/or application development roles (can be concurrent with data engineering experience) Soft Skills: Good verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders. Comfortable working in a fast-paced environment with changing priorities, technologies and tooling. Life-long learners will do well here. Demonstrated ability to work collaboratively within a team and across departments. Strong analytical and problem-solving skills. Benefits: TSG Equity compensation Full medical coverage Competitive compensation package and benefits: Generous leave and sabbatical policies 13th month bonus Smart, kind colleagues who are invested in your growth. Hybrid working environment Wellbeing stipend How to Apply Interested and qualified candidates should: Click here to apply online View all Jobs in Nigeria Lagos State Senior Data Engineer job vacancies in Nigeria