Senior Backend Engineer – Data Ingestion & ETL

Company - ListenFirst Media (social media analytics)

Location - Jaipur

Experience - 4–5 years in backend / data engineering

Type - Full-time

About the role

ListenFirst collects social and entertainment data from platforms like Facebook, Instagram, TikTok, YouTube, X and LinkedIn, then turns it into analytics for brands and media companies. You will own the backend that does this: the ingestion layer that collects the data, and the ETL pipeline that loads it into our Redshift data warehouse every day.

This is a hands-on role on a mature, production system. You will keep it running, fix data issues fast, and modernise it step by step.

What you will do

- Ingestion: Build and maintain collectors for social platform APIs (Facebook Graph, Instagram, TikTok, YouTube, LinkedIn and others). Handle API version changes, rate limits, auth and pagination.
- ETL: Own the extract-transform step that turns JSON ingest events into warehouse rows. Add new tables, fields and transformations through config, code and tests.
- Data warehouse: Write and tune Redshift SQL: migrations, views, incremental loads, COPY from S3, compression encodings, WLM and query performance.
- AWS operations: Run the pipeline on AWS: S3, SQS (priority queues), Kinesis Firehose, DynamoDB, CloudWatch, SNS and EC2 workers. Reprocess data, scale workers and recover failed runs.
- Data issues: Investigate data gaps and wrong counts raised by Support and Client teams. Find the root cause, fix it and backfill.
- Modernisation: Upgrade old libraries (e.g. AWS SDK v2 to v3), add tests where they are missing, move secrets out of code, and improve monitoring and alerts.
- Cost: Help reduce infra cost (Redshift, EC2) without losing data coverage.
- Team: Write explicit docs and runbooks. Review code.



Use AI coding tools (Claude Code or similar) in daily work.

Must have

- 4–5 years of backend or data engineering experience on production systems.
- Strong in Ruby, or strong in Python/Go and willing to work mainly in Ruby. Our ETL and ingestion code is mostly Ruby.
- Strong SQL. Hands-on with a columnar warehouse: Amazon Redshift preferred (Snowflake / BigQuery also fine).
- Built data pipelines that move large volumes: batch loads, incremental loads, deduplication, backfills.
- Hands-on AWS: S3, SQS, EC2, IAM, CloudWatch. Kinesis or DynamoDB is a plus.
- Integrated third-party REST APIs: OAuth, rate limits, retries, schema changes.
- Comfortable on Linux: SSH, bash, cron, logs, process management.
- Debugs production issues end to end, from a client complaint down to the raw record.
- Git, code reviews, writing tests (RSpec, pytest or similar).

Good to have

- Experience with social media platform APIs (Meta Graph API, TikTok, YouTube Data API).
- Redshift tuning: dist/sort keys, encodings, WLM, RA3 / Serverless.
- Go or C++ for performance-critical tools.
- Kafka, Athena, Jenkins or GitHub Actions, Capistrano.
- Experience modernising a legacy codebase safely.

How we will judge success

- First 30 days: Set up locally, understand the ingest → ET → Redshift flow, fix first data issue.
- By 90 days: Own daily ETL runs and recovery. Ship at least one new collector or ETL table end to end.
- By 6 months: Measurable gains in reliability, test coverage or cost. Become the go-to person for pipeline issues.

Interview focus

- SQL round: write and optimise warehouse queries; explain an incremental load.
- Pipeline design: design ingestion for a new social platform API, including failures and backfills.
- Debugging round: find why a metric dropped, using logs, S3 files and SQL.
- Code review: review a short Ruby or Python ETL change.

📌 Senior Backend Engineer (Jaipur)
🏢 ListenFirst
📍 Jaipur