Data Platforms • Backend • Cloud

Elena Manole

Big Data Engineer | Platform Engineer

I design and run reliable data platforms for analytics and product use cases. Most of my work sits at the intersection of backend services, streaming pipelines, and cloud infrastructure.

elenamanole1999@gmail.com +40 731 377 784 Bucharest, RO (Remote)

About

Big Data and Streaming Engineer with 5+ years of experience building large-scale data systems. I focus on robust ingestion, incremental processing, and production-grade orchestration with tools such as Spark, Kafka, Airflow, and AWS.

Core Strengths

Data Engineering

Streaming and batch pipelines, incremental models, data quality, and lineage-aware processing.

Backend Systems

Python/Go services, APIs, event-driven patterns, fault-tolerant jobs, and production observability.

Cloud & Platform

AWS-native architectures with orchestration, CI/CD integration, and infrastructure-minded system design.

Experience Highlights

Big Data Engineer · SearchPilot Via Remote.com

Aug 2023 — Present
  • Own core platform pipelines for analytics and experimentation.
  • Built Firehose ingestion and Googlebot/customer-event streams.
  • Tuned streaming and batch workflows for production stability.

Senior Data Engineer · Audience Data @ BBC

Feb 2022 — Aug 2023
  • Built and operated large-scale audience data pipelines.
  • Processed data with Apache Hudi and event-time windowing.
  • Automated interactions-attribution models for all sites.

Software Engineer @ BBC

Nov 2020 — Feb 2022
  • Implemented CI/CD and deployment security improvements.
  • Built event processing and internal tooling for data products.

Selected Side Projects

MT5 Multi-Timeframe Trading Signal Bot

Python · Data signals · Risk controls

Backend-oriented trading signal engine that consumes OHLC market data across multiple timeframes and outputs explainable BUY/SELL/NO_TRADE decisions with SL/TP levels.

  • Combined ADX, RSI, MACD, VWAP, and Fibonacci logic in a confidence-scored strategy.
  • Added periodic exporter for live notifications and reporting.
  • Improved signal stability with closed-bar entry logic and robust ATR-based stop-loss design.

Public Auctions Platform

Backend APIs · Data workflows · Reliability

End-to-end auction platform side project focused on backend architecture and data lifecycle: listings, bids, event handling, and reporting.

  • Designed data models and API flows for auction entities and bid state transitions.
  • Emphasized consistent validation, traceability, and predictable outcomes under concurrent updates.
  • Added analytics-ready exports to support operational reporting.

Tools & Technologies

Languages

Python Go Scala Java SQL Bash

Data & Streaming

Apache Spark Kafka Apache Hudi Apache Beam Airflow / MWAA

AWS Data Platform

EMR Glue Lambda Athena Redshift S3

Datastores & Delivery

PostgreSQL MongoDB Docker Jenkins

My Medallion Architecture

This is the Medallion architecture pattern I use in my own work to turn raw events into trusted, analytics-ready datasets and production-facing outputs.

Bronze

Raw events from APIs, trackers, and logs.

Silver

Validation, enrichment, dedupe, and session logic.

Gold

Analytics-ready models powering decisions.

Serving

Dashboards, APIs, and product features.

01 Capture reality

Reliable ingestion first. No assumptions, no dropped edge cases.

02 Make data trustworthy

Schema checks, late-arrival handling, and deterministic transforms.

03 Model for action

Domain-ready datasets for experiments, forecasting, and KPIs.

04 Deliver to users

Low-latency access paths that teams can depend on every day.

Let’s Build Reliable Data Systems

I am open to data platform, backend, and cloud engineering roles.

Contact Me