We are looking for a Senior Software Engineer to join our Data Engineering Infrastructure team, which builds and operates the foundational platforms that power data ingestion, transformation, and analytics across the organization. You will design and develop high-performance, reliable, and scalable systems that enable data engineers, analysts, and ML practitioners to move, process, and govern data efficiently and securely.

Description

As a Senior Software Engineer in the Data Engineering Infrastructure team, you will design and build distributed systems and frameworks that automate the lifecycle of data - from ingestion to transformation to serving. You'll work at the intersection of software engineering, distributed data processing, and cloud infrastructure, helping to define the standards, abstractions, and tools that enable our data platform to operate at scale.

You will collaborate closely with teams across data engineering, analytics, ML, and platform engineering to deliver resilient infrastructure components such as data ingestion pipelines, metadata and schema management services, workflow orchestration, and monitoring frameworks. This is a hands-on role where you will influence architecture, write production-grade code, and drive engineering excellence across the data platform.","responsibilities":"Design, build, and maintain scalable data infrastructure and frameworks supporting batch and streaming workloads.

Develop common services for data ingestion, schema evolution, metadata management, and data quality enforcement.

Implement automation for data pipeline deployment, monitoring, and governance.

Collaborate with data engineers and platform teams to define APIs, SDKs, and libraries that make developing data applications simpler and safer.

Improve performance, reliability, and observability of data pipelines and platform components.

Participate in architecture reviews, code reviews, and technical design discussions.

Drive adoption of best practices in distributed systems, storage formats (Parquet, Iceberg), and data access layers.

Contribute to capacity planning, cost optimization, and operational excellence in cloud and on-prem environments.

Mentor junior engineers and contribute to the overall technical strategy and roadmap for the data platform.

Preferred Qualifications

Deep expertise in optimizing and troubleshooting distributed data frameworks (e.g., Apache Spark internals, Flink stateful streaming, Kafka Connect)

Advanced experience with workflow orchestration tools (e.g., Airflow, Prefect, Dagster), including custom development

Proven track record in performance tuning, cost optimization, and designing comprehensive observability solutions for large-scale cloud data platforms

Familiarity with data security, privacy, and compliance principles within data infrastructure

Experience integrating data platforms with MLOps and machine learning workflows

Active participation or contributions to relevant open-source data technologies or industry communities

Master's or Ph.D. degree in Computer Science, Data Engineering, or a related quantitative field

Minimum Qualifications

12+ years of experience in software engineering, with at least 5 years focused on data systems or platform infrastructure

Proven track record of leading design discussions, mentoring engineers, and driving cross-team technical initiatives

Strong programming skills in Java, Python; Scala - nice to have

Hands-on experience designing, developing, and operating high-performance backend services

Hands-on experience with distributed data frameworks such as Spark, Flink, or Kafka

Solid understanding of data modeling, storage formats (Parquet/Avro/ORC), and partitioning strategies

Experience with data governance, cataloging, and schema management systems (e.g., Hive Metastore, Glue, Iceberg, Delta Lake)

Experience working with cloud-based data platforms (AWS, GCP, or Azure)

Experience building data infrastructure frameworks, SDKs, or shared libraries used by multiple data teams

Familiarity with CI/CD, container orchestration (Kubernetes), and infrastructure-as-code tools (Terraform, CloudFormation)

Excellent problem-solving, debugging, and communication skills

Bachelor's degree in Computer Science, Engineering, or related field (or equivalent practical experience)

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .

Pay & Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.