Software Engineering Specialist,Data Platform

Required Travel :Minimal

Managerial - No

Location: :Israel- RAANANA (Amdocs Site)

Who are we?

Amdocs helps the world’s leading communications and media companies deliver exceptional customer experiences through reliable, efficient, and secure operations at scale. We provide software products and services that embed intelligence into how work runs across business, IT, and network domains –delivering measurable outcomes in customer experience, network performance, cloud modernization, and revenue growth. With our talented people, and more than forty years of experience running mission-critical systems around the globe, Amdocs runs billions of transactions daily. Our technology is relied on every day, connecting people worldwide and advancing a more inclusive, connected world. Together, we help those who shape the future to make it amazing. Amdocs is listed on the NASDAQ Global Select Market (NASDAQ: DOX) and reported revenue of $4.53 billion in fiscal 2025. For more information, visit www.amdocs.com

At Amdocs, our mission is to empower our employees to 'Live Amazing, Do Amazing' every day. We believe in creating a workplace where you not only excel professionally but also thrive personally. Through our culture of making a real impact, fostering growth, embracing flexibility, and building connections, we enable them to live meaningful lives while making a difference in the world.

In one sentence

Cognitive Core Insights (CCI) is the group within Amdocs Cognitive Core responsible for delivering actionable AI-driven insights and recommendations on the aOS platform — Amdocs's open, telco-specific agentic AI platform. We build and operate the production systems that turn raw customer interactions into structured insights consumed in real time by downstream agentic experiences.

Our work runs on a modern data and ML platform — distributed processing on Spark, lakehouse storage on Iceberg and Delta, transformation in dbt, orchestration in Airflow, and serving through Postgres and FastAPI. We operate at the intersection of large-scale data engineering, applied ML, and production LLM systems. For more information, visit: https://www.amdocs.com/products-services/aos/cognitive-core.

We are looking for a highly-motivated software engineer to join the Platform team within CCI. In this role, you will design, build, and operate the production data and ML pipelines that power our customer-insight products — writing the code that ingests, transforms, models, and serves data at scale.

This is a hands-on engineering role focused on production reliability and delivery. You will own pipelines end to end — from design and implementation through deployment, monitoring, and iteration — and partner closely with data scientists, GenAI engineers, and the CCI architect to bring new use cases to life.

What will your job look like?

• Build and operate production pipelines. Design, implement, and own end-to-end data and ML pipelines — ingestion, transformation, model integration, and serving — that run reliably at scale on real customer data.
• Model data well. Define and evolve the data models that downstream teams consume — clean contracts, sensible grain, partition-aware design, and a clear story for how each table is produced and consumed.
• Write production-grade code. Build Python and SQL systems that are testable, observable, performant, and operable in production.
• Engineer for reliability, latency, and cost. Reason explicitly about data volumes, partition pruning, compute cost, and SLA boundaries; tune pipelines for correctness and efficiency.
• Own orchestration at production scale. Build and maintain orchestrated workflows with proper dependency management, idempotency, retries, watermarking, and observability.
• Integrate ML and LLM systems. Land model and LLM outputs as well-modeled data products consumed by downstream insights and APIs; partner with data scientists and GenAI engineers on integration boundaries.
• Raise the engineering bar. Contribute to design reviews, define internal standards for pipeline development, and share knowledge with peers.
  
  

• 5+ years of hands-on software engineering experience, preferrably on data platforms, with a track record of shipping and operating production systems at scale.
• Degree in a quantitative or engineering field (Computer Science, Mathematics, Physics, Electrical Engineering, or equivalent).
• Strong Python and SQL: production-grade code with modern Python practices (testing, type hints, packaging, performance awareness.
• Hands-on experience with distributed data processing (Spark or equivalent) on real production workloads.
• Solid grounding in data modeling: multi-layer architectures (Bronze/Silver/Gold), partitioning strategies, and incremental processing patterns.
• Experience with modern transformation tooling (dbt or equivalent) and lakehouse formats.
• Experience operating production workflow orchestration (Airflow or equivalent), including dependency management, idempotency, and recovery.
• Production discipline: comfortable with observability (logs, metrics, traces), debugging from real telemetry, and iterating based on production signal.
• Engineering fundamentals: Git, CI/CD, containerization, and comfort operating workloads in a cloud environment.
• Strong communication in English (verbal and written); able to engage technical and business stakeholders.
  
  

• Experience building pipelines that serve ML or AI systems - feature engineering, training/inference data, model output integration.
• Familiarity with GenAI / LLM systems - enough to build pipelines that feed prompts, store structured outputs, and integrate LLM results into downstream tables.
• Hands-on experience on Google Cloud Platform (GKE, Cloud SQL, GCS) or Databricks.
• Telco domain knowledge - BSS/OSS systems, customer interaction data, contact-center analytics.
  
  

• Experience with Iceberg specifically (hidden partitioning, schema evolution, time travel).
• Experience with PostgreSQL as a serving layer for analytical or ML outputs.
• Hands-on experience with modern AI coding tools (Cursor, Claude Code, Copilot, or equivalent) as a productivity multiplier.
  
  

• You will own meaningful production systems that directly power customer-facing AI experiences for global telco operators.
• You will work at the intersection of large-scale data engineering, ML, and GenAI - a combination that is genuinely rare in production environments.
• You will have clear technical ownership and room to influence engineering standards across the platform.
• You will be part of a team that ships real products to real customers, with the feedback loops that come with it.