Sr. Application Solution Architect

Owning the end-to-end solution architecture

of the Daitics AI CDP: a sovereign, on-prem, telco-native Customer Data

Platform built on a streaming architecture, deployed on infrastructure we run

ourselves (Kubernetes, Helm), not managed cloud services. The platform

processes hundreds of thousands of events per second across thirty or more

source systems and delivers unified customer profiles for B2C persons and B2B

organizations, accounts, sites, lines, devices and contacts. You will own the

architecture across the five planes (Authoring, Control, Data, Activation,

Observability) and the five layers (atomic events, tile primitives, trait

values, signal filters, signal events), hold the line on architectural

principles across engine boundaries, and translate them into designs

engineering teams can build against.

Requirements

• 12+ years

in software and data engineering, with at least 5 years owning solution or

platform architecture for large-scale distributed systems

• Demonstrated

ownership of end-to-end architecture for a streaming data platform on

self-managed infrastructure (on-prem or private cloud) topology, state

placement, failure domains, cutover, and capacity, not documentation alone

• Deep,

hands-on architectural command of Apache Flink as a stateful streaming runtime DataStream and SQL, keyed state on RocksDB, broadcast state for configuration

distribution, Async I/O for external lookups, checkpoint and savepoint

discipline, and failure isolation across independent job clusters (core

requirement)

• Proven

ability to design two-tier latency architectures: a millisecond-level hot path

against a minute-level durable cold path, with an explicit end-to-end latency

budget and a documented inclusion and exclusion list

• Experience

designing Kafka topologies for multi-tenant platforms topic taxonomy,

partition-key selection and partition sizing, compacted control streams,

retention classes, and enforced naming conventions

• Experience

architecting schema governance across producers and consumers Avro or

equivalent through a schema registry, compatibility modes, and coordinated

promotion of breaking changes

• Hands-on

architecture experience with lakehouse table formats (Apache Paimon, Iceberg,

Delta Lake, or Hudi) on S3-compatible object storage - primary-key and LSM

table design, partitioning, compaction, snapshot expiry, and separation of

streaming from batch read paths

• Experience

designing governed single-writer patterns where many producers write to one

substrate through one consolidating service, with per-stream configuration

applied without restarts and exactly-once-effective semantics

• Experience

with distributed in-memory caches (Apache Ignite, Hazelcast, Redis, or similar) partitioned versus replicated tables, affinity colocation with the compute

layer, thin-client access patterns, operator-local caching, and cross-consumer

invalidation

• Ability to

define and enforce a state-placement decision framework: broadcast state versus

keyed state versus external cache versus first-seen load, with explicit rules

rather than case-by-case judgment

• Experience

designing aggregation architectures that serve arbitrary rolling windows with

sub-millisecond reads while keeping state bounded and recomputable

(pre-aggregated tiles, multi-resolution granularity ladders, or equivalent),

including approximate aggregation through sketches (HyperLogLog, t-digest,

count-min) and honesty about their limits

• Experience

architecting identity resolution at scale deterministic and probabilistic

matching, identity graph modeling, effective-dated B2B relationships, merge and

split workflows, anonymous-to-known stitching, and downstream propagation of

identity change

• Experience

modeling entity lifecycle state machines in streaming systems, including

identifier reassignment, quarantine, archival, and purge, with auditable

transitions

• Architecture

experience with consent enforcement and data governance configurable

enforcement modes, data usage labeling and enforcement, policy distribution to

the runtime, and enforcement designs that avoid a synchronous service call per

event

• Experience

architecting tokenization, hashing, masking, and encryption for sensitive

identifiers - reversible versus irreversible choices, key versioning and

rotation (HashiCorp Vault Transit or equivalent), protection applied at the

ingest boundary, and audited just-in-time detokenization at delivery

• Experience

designing end-to-end lineage and edit-time impact analysis artifacts and

dependencies modeled as a graph, forward and reverse traversal, and prevention

of orphaned dependencies on delete, rename, or semantic change

• Experience

designing versioned artifact activation and cutover across engine boundaries

grace windows, transition emission policy, late-event windows, and rollback

• Ability to

reason about state reconciliation when a computation definition changes forward-only, full or partial recalculation, parallel versions, evacuate and

rebuild, snapshot seeding and how data retention constrains which options are

valid

• Experience

designing multi-tenant isolation on Kubernetes namespace and resource

topology per tenant and workspace, noisy-neighbour control, per-tenant storage,

secrets, and cross-workspace sharing contracts

• Experience

architecting authentication, authorization, and network security enterprise

IdP federation (OIDC, Keycloak or equivalent), attribute-based access control,

Kubernetes NetworkPolicies for east-west isolation, service-mesh mTLS, and

secrets management

• Experience

defining failure domains, SLOs, RPO and RTO targets for streaming platforms,

and designing replay, backfill, and reconciliation paths that do not re-trigger

external actions

• Ability to

size a platform of this shape end to end: from events per second and subject

counts to partitions, parallelism, keyed state size, cache footprint, and

storage - and to validate the model against measured behaviour

• Judgement

on when to wrap an open-source component behind a stable platform service

interface with pluggable implementations, and when to depend on it directly

• Experience

with a canonical or industry semantic model and the discipline of preventing

semantic drift; telco experience with TM Forum SID and TMF620 is a strong

advantage

• Experience

integrating ML into a streaming platform models upstream of derived

attributes, online and batch scoring paths, training-serving consistency, and

keeping inference off the hot path unless benchmarked

• Practical

experience with Spring Boot on Java for control-plane microservices, PostgreSQL

as a definition store, and workflow orchestration (Temporal, Argo Workflows, or

equivalent) with BPMN approval flows (Flowable, Camunda, or equivalent)

• Experience

with observability stacks (OpenTelemetry, Prometheus, Grafana, distributed

tracing) and with defining what operators actually need to see

• Familiarity

with graph and vector substrates for lineage, relationship traversal, and

semantic similarity over platform metadata

• Ability to

author and maintain a layered architecture corpus a master blueprint with

component annexes, explicit design rules, and cross-document consistency and

to defend it in architecture review

• Familiarity

using AI tools for design, development, and debugging (Claude, Cursor, Codex)